Perceptual Serendipity

AN APTITUDE FOR PERCEIVING PLEASANT DISCOVERIES ON AN ACCIDENTAL BASIS

AN APTITUDE FOR PERCEIVING PLEASANT DISCOVERIES ON AN ACCIDENTAL BASIS

Scott McIntyre Townsend B.Arch.Sci Ryerson University 2018

A design thesis project presented to Ryerson University in partial fulfillment of the requirements for the degree of Master of Architecture in the Program of Architecture Toronto, Ontario, Canada, 2018 © Scott M. Townsend 2018

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AUTHOR’S DECLARATION FOR ELECTRONIC SUBMISSION OF A THESIS I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, including and required final revisions, as accepted by my examiners.

I authorize Ryerson University to lend this thesis to other institutions or individuals for the purpose of scholarly research.

I further authorize Ryerson University to reproduce this thesis by photocopying or by other means, in total or in part, at the request of other institutions or individuals for the purpose of scholarly research.

I understand that my thesis may be made electronically available to the public.

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Figure â„– 01: Sketch from author. Digital simulation that fortifies the notion of unlimited perceptual models founded within simulated reality.

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Abstract Perceptual Serendipity M.Arch 2018 Scott Townsend Master of Architecture Ryerson University Serendipity, or serendipitous behaviour, is described as the aptitude for perceiving pleasant discoveries on an accidental basis. While not a new concept to design and its related process, serendipitous discovery within the perceptual process of design is an incredibly potent catalyst for the designer. As an introspective exercise, observing this serendipitous behaviour through the lens of various allegorical simulatons will allow us to take a step back and apprehend new modes of vision.

The perceptual process, within tectonic and spatial understanding, is a fleeting experience to apprehend. This process, the concept of cognitive model-making and real-time model generation, is holistic by nature. The idea of serendipitous discovery through this experience becomes a metaphorical vehicle for us to observe the cognitive components themselves.

This thesis will explore these serendipitous discoveries as stand-alone models, or simulations. Albeit fluid through firsthand experience, they become key for the investigative process in which one can begin to understand the drivers for the models we make of our environment.

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Acknowledgments

This thesis would simply not have been possible without the action of my committee.

First and foremost, my supervisor Arthur Wrigglesworth has been an incredible supporter of my work and my ability (or inability) to portray my conceptual ideas. He has gone above and beyond all circumstances as an educator to see this thesis through and for that I will always be grateful. Arthur has been a professor and mentor to me in some form or another for almost a decade, and has helped me through my highest highs and lowest lows.

Secondly, I would like to thank Dr. John Cirka and Mimi Lam, masters program director and administrator respectively. Without the administrative support and understanding they have provided, this thesis submission would not have been possible.

I would also like to thank my second reader, Professor Vincent Hui, for being an outstanding educator and friend for the entirety of my studies at Ryerson.

I would also like to thank Bill and Mary Lynne Rowe for their incredible support, as well as always being available to discuss ideas. Lastly, I would like to thank my three brothers, and especially my parents. They have been supportive of my health and wellbeing since I began this journey, not matter the cost or obstacle.

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Table of Contents Author’s Declaration Abstract Acknowledgements

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List of Figures Introduction Perceptual Serendipity Allegorical Simulation Rediscorvery

1.1 1.2 1.3

The Visual Field Fovea Scotoma Periphery Perception Visual Perception Cognition

2.1 2.2 2.3 2.4 2.5 2.6

Signal Processing Pre-Aliasing (Sampling) Filter Aliasing Error Reconstruction Digital Secretion

3.1 3.2 3.3 3.4 3.5 3.6

Simulation №1 Umwelt Visual Fidelity Recognition

4.1 4.2 4.3

Simulation №2 Reference Drilling Cognitive Jamming

5.1 5.2 5.3

Simulation №3 Seeing Photogrammetry Peripheral Reconstruction

6.1 6.2 6.3

Simulation №4 Re-cognition Cognitive Model Making

7.1 7.2

Conclusion Serendipitous Perception

1.0

Page 1 Page 1 Page 2 Page 3

2.0

Page 6 Page 6 Page 11 Page 19 Page 23 Page 30 Page 36

3.0

Page 38 Page 38 Page 42 Page 45 Page 46 Page 47 Page 48

4.0

Page 51 Page 51 Page 55 Page 60

5.0

Page 62 Page 62 Page 62 Page 64

6.0

Page 69 Page 69 Page 74 Page 81

7.0

Page 82 Page 82 Page 85

8.0

Page 89 Page 89

Lexicon of Terms

Page 90

Works Cited

Page 94

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List of Figures

Figure № 01 Page V

Simulation sketch.

Sketch concept from author. Digital simulation that fortifies the notion of unlimited perceptual models founded within simulated reality.

Figure № 02 Page 04

Modded landscape.

Landscape of digital environment. Original image courtesey of Spanish PC modder ‘Unreal’. http://www.asot.es/2001/09/skyrim-mods.html

Figure № 03 Page 04

Regatta landscape.

Regatta landscape, perspective projection. Oil on Canvas, courtesy of Michael Webb and the Graham Foundation. http://www.grahamfoundation.org/grantees/5183-two-journeys

Figure № 04 Page 06

Foveal cones.

Collage from author. Foveal cones extracted from the Landschaft in order to provide sites for the perceptual simulations.

Figure № 05 Page 09

Ice core.

Images from Michael Webb’s ‘Temple Island’. Courtesy of the AA and Victoria University’s school of Computational Design and Landscape Architecture. http://timekept.tumblr.com/image/20208403527

Figure № 06 Page 10

Regatta shadows.

Images from Michael Webb’s ‘Temple Island’. Courtesy of Christina Godiksen and Nina Gerada of Unit H. http://unit-h-culturalgeometries.blogspot.ca/2013/10/on-dr awingpart-one.html

Figure № 07 Page 12

Scintillating Scotoma.

Image from Author. Example of visual degradation during the event of a scintillating scotoma.

Figure № 08 Page 12

Scintillating Scotoma. (Zoom) Image from Author. Partial pixelated zoom of Figure 07. Showcasing slight degeneration of visual language from the tools used to represent the image.

Figure № 09 Page 14

Hemispatial Sketches.

Illustrations by patients experiencing hemispatial neglect. Typical examples of axis degradation as shown by the clock face, as well as range degradations shown by the lack of three-dimensional replication in the cube and house samples. (Right) Courtesy of the Journal of Neurology, Neurosurgery & Psychiatry. http://jnnp.bmj.com/content/jnnp/68/1/106/F1.large.jpg?

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List of Figures

Figure № 10 Page 17 Figure № 11 Page 17

Figure № 12 Page 20 Figure № 13 Page 21 Figure № 14 Page 22 Figure № 15 Page 26

Figure № 16 Page 27

Figure № 17 Page 28 Figure № 18 Page 29 Figure № 19 Page 31

Piazza del Duomo.

Photocrom recolouring print by Photoglob Zurich, between 1890 and 1900. Piazza del Duomo (Cathedral Square), Milan, Italy, ca. 1895. http://loc.gov/pictures/resource/ppmsc.06546/

Neglect as Illustration.

Illustration describing the experience of a neglect patient as a result of the study conducted in Milan. Courtesy of Daniela Ovadia. https://www.cerveauetpsycho.fr/sd/histoire-neurosciences/hemineglig ence-lexperience-de-la-place-fantome-9314.php

Peripheral Obfuscators.

Peripheral study done by Jonsson, taking care of scan data drawn from the periphery of view. http://cargocollective.com/birgirjonsson/Periphery-Studies

Peripheral Scanning.

LiDAR scanning done by Jonsson, modelled according to fields of vision attracted by peripheral armatures. http://cargocollective.com/birgirjonsson/Islands-of-Vision

Peripheral Interventions.

Peripheral interventions, physical model. Made as physical studies for the peripheral armatures. http://cargocollective.com/birgirjonsson/Islands-of-Vision-models

Simulated Landschaft.

Landscape of digital environment. Original image courtesey of Spanish PC modder under the moniker of ‘Unreal’. Second image edited by author including new percept for simulated study. http://www.asot.es/2001/09/skyrim-mods.html

Waterfall.

M.C. Escher, Waterfall. 1961 lithograph. Early example of a form of multistable perception induced through the representation of the content within the drawing. http://www.mcescher.com/gallery/recognition-success/waterfall/

Monument Valley.

Modern examples of imagery inspired by the work of M.C. Escher, found in the iOS game called Monument Valley. https://ustwo.com/work/monument-valley

Multistable Percept.

From author, multistable perception investigations using percept, physical model in digital collage.

Lavender Percept.

From author, early distal object exercise. Bottom image shows a reconstruction after given hundreds of image data entries. The object begins to dissolve in some moments, and capture the environment in others.

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List of Figures

Figure № 20 Page 32

Type Aliasing.

The bottom image shows the aliasing applied to the above text. As illustrated, the aliasing process approximates and samples values to smoothen the ‘jaggy’ edges for a higher fidelity replication. https://www.cell.com/fulltext/S0896-6273(00)80826-0

Figure № 21 Page 33

Black Tree.

From author, another distal object exercise done with a physical model of ‘The Black Tree’, perched over a blue quilt.

Figure № 22 Page 35

Black Tree Model.

From author, physical model orientation of ‘The Black Tree’ for initial perceptual simulations.

Figure № 23 Page 39

Dalmation.

Image of a Dalmation. A classic example when discussing emergence within the realm of Gestalt Theory. Digital. https://www.cell.com/fulltext/S0896-6273(00)80826-0

Figure № 24 Page 39

Acrylic Forms.

From author, physical model. Acrylic forms cast for signal processing samples.

Figure № 25 Page 41

Acrylic Scans.

From author, three seperate digitizations of the acrylic-cast models prior. Prioritization and layout determined by the scan and left untouched for representation.

Figure № 26 Page 41

Moire Pattern.

Bottom image shows a poory down-sampled image of the above brick wall, resulting in a moire pattern being observed through the display.

Courtesy of Colin M.L. Burnett.

Figure № 27 Page 47

Surface Error.

Models from Matthew Shaw’s Surface Error project on display, showcasing the buildup of layered scan data and the reproduction of each piece. http://we-make-money-not-art.com/subverting_the_lidar_landscape/

Figure № 28 Page 48

Mail Rail.

Layered data clouds from a subway tunnel beneath the streets of London England. Digitally stitched together from various scans of the site by ScanLab Projects. https://www.wired.com/2015/04/laser-scans-london-new-way-see-world/

Figure № 29 Page 49

Limbo.

The above images are from the series entitled ‘Limbo’ by the design firm ScanLab. The images are a classic component to the work of the studio, in which collaging different data sets into an image provide a previously unforseen correlation (or sometimes even isolation) between different visions of architectural space. Courtesy of ScanLab Projects. https://scanlabprojects.co.uk/work/guardian-limbo/

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List of Figures

Figure № 30 Page 50

Figure № 31 Page 54

Figure № 32 Page 56 Figure № 33 Page 57

Figure № 34 Page 58 Figure № 35 Page 59 Figure № 36 Page 61 Figure № 37 Page 63 Figure № 38 Page 64 Figure № 39 Page 65

Percept Location.

Landscape of digital environment. Original image courtesey of Spanish PC modder ‘Unreal’. Image is focused on what will be the location of the percept for simulations 1 through 4. http://www.asot.es/2001/09/skyrim-mods.html

Sight Lines.

Images courtesy of ScanLab and the New York Times, constructed vision of a self-driving automobile. This scanning method aimed to portray a new mode of vision, previously unseen by pedestrians. https://vimeo.com/145248208

Environmental navigation. (1) From author. Physical model super-imposed on the possible environment. Specific tree was selected for this study due to its location bordering multiple environmental conditions.

Environmental navigation. (2) From Author. Image views based on previous set, with image retouching done do enhance visual and graphic fidelity. Digital insertion of the photographed percept much more integrated into the image.

Distal Object. (1) From Author. Image showcasing the blend of visual fidelity and serindipitous interaction when left to rest within the umwelt, as a result of the physics implemented by the digital tool.

Distal Object. (2) From Author. Image showcasing the blend of visual fidelity and serindipitous interaction when left to rest within the umwelt, as a result of the physics implemented by the digital tool.

Viewing Investigation.

From author. Different methods of ‘viewing’. Digital scans done with different techniques to study aliasing and nuances behind each one.

LiDAR Jammer.

From author. Different methods of ‘viewing’. Digital scans done with different techniques to study aliasing and nuances behind each one. http://www.bldgblog.com/2011/04/stealth-objects-and-scanning-mist/

Jammed Scanning.

Scans as a result of LiDAR jamming, disorienting the language of the reconstruction induced by the various stealth jammers. http://www.bldgblog.com/2011/04/stealth-objects-and-scanning-mist/

Black Mesh.

From author. Mesh generated by the Black Tree, chunks of the umvelt are baked into the structure of the object due to referential treatment during aliasing., only possible after adding hundreds of data entries for the object to be visible to the scan.

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List of Figures

Figure № 40 Page 66

Figure № 41 Page 67

Figure № 42 Page 68 Figure № 43 Page 69

Figure № 44 Page 71

Figure № 45 Page 73 Figure № 46 Page 75 Figure № 47 Page 77 Figure № 48 Page 78 Figure № 49 Page 79

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Islands of Vision.

From author. Various simulations and cognitive models observed throughout the simulated perceptual process. The various anomalies and phenomena will prove serendipitous in nature as data passes from site to site.

Umvelt Jamming.

From author. Above, an image of various jammed components to the reconstruction of the umvelt through the eyes of the scan. The distal object interacts heavily with the mapping of what tie-point data is influencing the data that is sampled. Below shows a series of images, a small portion of hundreds take of the umvelt in order to provide sites for the perceptual simulation.

Anthropomorphic Cloud.

From author. Zoom-in of anthropomorphic point cloud. Physical model of the distal stimulus on blue quilt was digitized for point cloud and colour data sampling.

The Key to Dreams.

From surrealist painter Rene Magritte, The Key of Dreams plays on the commentary that there is always a culture of language present between words and seeing. https://courses.washington.edu/hypertxt/cgi-bin/book/wordsinimages/ wordsin.html

Percept Placement.

From author, sketches and overlays of percept to be studied under the perceptual simulations. Initial concept of the design to interact with the fidelity of the environment. Below: Digital umvwelt test setting, providing a high-fidelity environment to conduct simulations within each dedicated site.

Scanning Romanticism.

Images from the work of ScanLab, investigating the romanticism behind scanning as a mode of vision. Berlin. http://www.bldgblog.com/2014/04/romanticism-of-the-scanning-error/

Photogrammetric Umvelt.

From author. Results of a photogrammetric scan of the Umvelt, providing a new language to perceive the environment.

Tie-Point Display.

From author. Tie-points displayed after the image culling occurs for the photogrammetric system.

Photogrammetric Series. (1) From author. Point cloud scans of the first iteration percept, (purple) accompanied by views from the photogrammetric build identified by blue viewport rectangles.

Photogrammetric Series. (2) From author. Point cloud scans of the second iteration percept, (black) accompanied by views from within the original Landschaft correlating to the angle views within the point cloud. These views are now considered their own umwelt for further investigations within the sites.

List of Figures

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Figure № 54 Page 84 Figure № 55 Page 85 Figure № 56 Page 87 Figure № 57 Page 87 Figure № 58 Page 88 Figure № 59 Page 89

Photogrammetric Technique.

From author. Different photogrammetric approaches were taken in an attempt to understand the digital language of the simulation. Various techniques in image identification were fed as data samples for the system.

Peripheral Reconstruction.

From author. Reconstruction of the black tree serving as a distal object.

This discovery was only made visible by navigating within the digital space. Other previews of the percept did not share the same characteristics, and was discovered by a serendipitous walkthrough of the Landschaft.

Point Data.

From author. Tie-point and point cloud data overlay.

Topographical Ties.

From author. These topographical studies were done to discern the relevency of certain tie-point weight values. As certain tie-point values are culled from the perceptual simulation, others are identified as stronger corrolaries between certain views. Two sets of images comparing the tie-point constellations to the corresponding topographical investigations. Tie-point prioritization within the perceptual simulation is used as a sampler when discerning the relevancy of perticular points.

Cognitive Anomoly.

From author. Images of a previously unforseen error in the construction of the distal object, only made visible by traversing the digital umvelt.

Cognitive Model.

From author. Example of a perceived cognitive model derived from layering previous models provided by the simulation.

Topographical Weight. (1) From author. Investigative drawing of tie-point weight speculation, providing a more three-dimensional approach to the foveal cone that protrudes from the site.

Topographical Weight. (2) From author. Further investigations regarding other data samples, ultimately rendering the amount of usable ‘sites’ infinite.

Landschaft Multiplicity.

From author. Visual cones extracted from the landschaft. These cones serve as various sites for each simulation.

Landschaft Multiplicity.

From author. An example of how the layering of these serendipitous discoveries could influence the way the designer interacts with the new cognitive investigations.

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PERCEPTUAL SERENDIPITY An aptitude for perceiving pleasant discoveries on an accidental basis.

-Definition adapted by author.

1.0 INTRODUCTION 1.1 Perceptual Serendipity

Serendipity, or serendipitous behaviour, is described as the aptitude for perceiving pleasant discoveries on an accidental basis. This definition, adapted by the etymological description published by Merriam-Webster, is born from an ethereal tale of discovery by happenstance. (MerriamWebster’s Collegiate Dictionary, 11th Edition, 2009) While not a new concept to design and its related process’, serendipitous discovery within the perceptual process of design is an incredibly potent catalyst for the concepts being explored within this thesis. The perceptual process of design is a natural and ongoing dialog between the way the individual or user perceives their surroundings based on a multitude of factors. As described by Schacter in his seminal document titled Psychology, perception is the “organization, identification, and interpretation of sensory information in order to represent and understand the presented information, or the environment.” (Schacter, 2011). While this definition provides a very pragmatic way of describing the actual process of perception; a designer’s capability to understand perception through design is a very powerful, as well as an ephemeral tool for developing an understanding of our environments. One of the most important things to note however, is that the idea of perception - when discussing the act of cognition - may not simply deal with sensory input. There are different schools of thought on the creation of a user’s cognitive models and how they are put to work, and within this thesis some of these will be explored. As an introspective exercise, observing this serendipitous behaviour across various simulations allows us to take a step back and apprehend new discoveries as we wade amongst the many aliases induced by simulated perception.

Simulated perception is a process that drives the discoveries of this thesis. As described, the perceptual process is very introspective in nature, and gives us access to a particular point of view that is very common when dealing with the process of experiencing design and its environments. A simulated version of this process however,

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offers a new perspective on the way in which we can study the process in motion, from an unbiased point of view. As a result, we can observe how these discoveries impact the way we perceive our surroundings as a whole. In order to properly observe and critique the perceptual process from an unbiased perspective, we must first remove ourselves from the typical notion of experience and look inward.

The perceptual process, within tectonic and spatial understanding, is a fleeting experience to apprehend. This process, the concept of cognitive model-making and real-time perceptual generation, is holistic by nature. In conjunction, these serendipitous discoveries, as stand-alone models become key for the investigative design process in which one can begin to understand the drivers for the models we make of our environment.

1.2 Allegorical Simulations

In order to properly observe and critique aspects of the perceptual process from an unbiased perspective, one must first remove oneself from the notion of first-hand perceptual experience and look inward. The topics discussed within this body of work will present a series of discrete investigations that will serve as allegorical simulations of direct perceptual experience, and the simulated relationship with the design process.

At its core, an allegory is an extended metaphor. The Merriam-Webster dictionary describes extended metaphors as simulated objects, environments, participants, and actions participate in a narrative that extends beyond their initial appearance. (Merriam-Webster’s Collegiate Dictionary, 11th Edition, 2009) These components in turn become equated with meanings that lie outside of the narrative itself, and personify the abstract ideas that they convey. Tracing back to the Greek term allegorein, or ‘to speak figuratively’, the key concept of the definition stems from the truth in which the simulations convey; a truth that directly portrays human conduct of experience.

For example, the digital scan, as an allegorical armature for ‘seeing’, offers a way to conceptualize spaces and forms in terms of saturation and density; very much akin to peripheral vision. Most importantly, the discussion of saturation and density go hand in hand when discussing the relationships between peripheral and foveal vision. Bob Sheil, a professor at Bartlett and editor for the Winter edition of AD

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in 2014, discusses this idea extensively within the context of digital scanning and ‘high definition’. The idea of exploring the peripheral components of vision are investigated through digital environmental scans, where saturation and density move to the forefront of understanding the digital scan as a new mode of vision. (Sheil, 2014) Spatially, we can observe how forms compose the environment in a more dispersed format, compared to the strict focus that foveal vision provides. This also allows us to dismantle the dominance of privileged form and to focus on the notion of perception through simulated experience. Conceptually, this technique is more in tune with our spatial perception within the fidelity of natural environments (Umwelten), in which our focal points and lines of reference naturally degrade, in favour of heightened peripheral awareness. (Sheil, 2014) 1.3 Re-Discovery

The topics discussed within this body of work will be presented through a series of discrete investigations that will serve as allegorical simulations of direct perceptual experience. The relationships between experiences discovered within the design process will also be explored through an ongoing dialog with the simulations themselves.

For the sake of our simulations, we will utilize a coopted digital landscape as our perceptual environment, shown in Figure 02. This particular environment is co-opted from a graphic engine, specifically used for its simulated ‘natural’ surroundings and high fidelity characteristics, both in image quality and in environmental subject. What is important to note moving forward is that this environment, as we peel its aliases apart within our various simulations, becomes our site for design investigation. Each of these aliases are the reconstructed moments in which the simulation interprets the environment, and studying the layering or de-layering of these aliases becomes a key activity when on the path to discovering a new cognitive model. The idea of using these moments as ‘sites’ is explained further in the work.

The utilization of the image as a site is a concept thoroughly explored by Archigram’s Michael Webb, in works such as The Journey. (Webb, 2014) Webb produces imagery derived from observing the environment as his site for discovery through introspective activity. Similarly, within this thesis, the idea of the site will be observed from the perspective of its image through introspective activity.

In Webb’s most recent re-visitation of The Journey, the

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Figure No.02 Landscape of digital environment.

Original image courtesey of Spanish PC modder ‘Unreal’.

Figure No.03 Regatta landscape, perspective projection. Oil on Canvas, courtesy of Michael Webb.

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foveal cone is preserved as a distilled object within the field of purview, and separated from what he calls the Landschaft.

(Webb, 2014) The field of purview is a term that Webb uses to describe the scene for his ‘sites’. Purview, as described from the Mariam-Webster definition, incorporates a “range of vision, understanding, of cognizance”, (Merriam-Webster’s Collegiate Dictionary, 11th Edition, 2009) pertaining to the range of experience or thought when isolating the foveal cone as the subject of his initial study. The concept of the purview is important as it inherently incorporates understanding in conjunction with the range of vision. As an exercise, Webb metaphorically distills the scope of the foveal cone, thus removing it from the overall Landschaft, to be investigated independently. (Figure 03) As such, the image of the foveal cone becomes the site for the self-titled Journey that is used as a source of dialog over the course of his project. While utilizing a series of Landschaft as our own, (Figure 04) we attempted to replicate this exercise as a basis for our own discoveries, in the form of several simulated perceptual experiences. In our case, the high visual fidelity of the image will play a major role in degrading lines of sight, and will further the saturation of vision offered by the scan. This cue (fidelity) will be the initial step to observing aliases produced by the scanned data, and offer a point of insertion for the design of our own percept. Fidelity as a concept will be thoroughly explored within Simulation No.1, as a precursor to the design of the architectural percept.

Overall, this simulation study will heighten our understanding of a new perceptual process, and encourage embracing serendipitous discovery within a design process.

This notion of re-discovery is important to discuss due to the serendipitous nature of observing our own behavior. It offers us access to reasons why we may exclude or include certain data when observing the environment, especially when fidelity is considered a major factor for the composition of our Landschaft.

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Figure No.04 Collage from author. Foveal cones extracted from the Landschaft in order to provide sites for the perceptual simulations.

2.0 THE VISUAL FIELD 2.1 Fovea

The discussion surrounding the traditionally understood field of vision is an interesting dialog that begins to unfold the concepts of perception as phenomenon that the simulations presented in this work aim to interpret.

In terms of the visual system, the foveal component of the human eye is the only part of the retina that permits one hundred percent visual acuity. (Hunziker, 2006) As noted in the work of Swiss psychologist Hans-Werner Hunziker, the line-of-sight is a virtual line that connects the fovea with a fixation point in the participant’s environment. He notes that the discovery of the line-of-sight is attributed to Leonardo da Vinci, who derived his insights through optical modelling and, more importantly, through exercises of introspection.

Latin for pitfall, the fovea is a small, central depression composed of photoreceptor cells that sends approximately half of all information through the optic nerve. (Rowe, 2017) That is, half of all information that the optic nerve receives comes from the foveal cells themselves, while the other half of the information is received from the rest of the retina. This is important to note due to the privilege of information being almost exactly equal to all other incoming information outside of the foveal cone. One would imagine initially, that the dominating clarity of the foveal cone would consume a much broader bandwidth of information, but the amount of peripheral information being processed is equal. In essence, the fovea

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is responsible for sharp central vision, which operates for the purpose of absorbing direct visual information. There are many works that document the basic function of the fovea, or ‘visual cone’ dating back to the studies of da Vinci, who is credited for providing the modern distinction between foveal and peripheral vision. (Palmer, 2002)(Shimamura et. al 2014)

In a similar thread, the work of Archigram founding member Michael Webb gives us access to an introductory discussion on the visual cone as an ‘ice core’ (Webb’s nomenclature for the foveal cone), casting ambiguous virtual shadows and providing a site for what Webb describes as The Journey. (Webb, 2014) This concept, in short, is the idea of using imagery derived from his studies as ‘sites’ of exploration for certain spatial and introspective activities. The distinction needs to be made in order to avoid the traditional definition of a site. In architectural discourse, the concept of a site traditionally references a location, surrounding, or a resting place that the user or architectural object inhabits. It is often also referred to as a ‘natural’ (possibly man-made) environment where the architectural design resides and, in some cases, interacts with on a physical and cultural level.

Webb’s landschaft project is a perfect example of discovery through introspective activity, and allows us access to certain perceptive models only achievable through introspective exercises such as those conducted in Simulation No. 3. This, in turn, shifts the concept of a designer’s site into an image of a landschaft, rather than a distinct environmental location.

The Journey is a long-standing narrative that begins with the concept of ‘capture’. Traditionally, the concept of ‘capturing’ a scene close to oneself would be through some sort of alchemy. (Webb, 2014) This ‘alchemy’, refers to both the technological revolution of photography, as well as the traditional (and quite analog) conjuration of perspective paintings and drawings. As noted by Webb, the author or photographer persuasively flattens onto a two-dimensional surface, the as yet unperceived and quite possibly fugitive, essence of the three-dimensional subject. To capture however, is also to take possession of, through what Webb describes as the ‘grokking’ that is brought about through drawing. (Webb, 2014) This science-fiction terminology reference is a strong influence on a large body of Webb’s introspective exercises.

The term ‘grokking’ was created by Robert A Heinlein, also known as the ‘dean of science fiction’. The word first appears in his book Stranger in a Strange Land, which carried a large significance to ‘being one with’ or whollistically learning

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through doing. The Oxford English Dictionary definition is ‘to understand intuitively or by empathy; establish rapport with’.

(Oxford English Dictionary, 7th Edition, 2006) In essence, ‘grokking’ describes a sense of understanding or discovery through the act of interacting with, in Webb’s case, the drawing.

The landscape (or environment) that The Journey occupies is that of the regatta course at Henley-on-Thames, and more particularly, the volume of air, land and water enclosed by a perspectival cone of vision whose axis is parallel to the plane of the river and whose apex is the ‘Cyclopean eye of the beholder’. Another fantasy reference, described

by Webb as the technological limitation of the revolution of photography, offers a very strong diagrammatic visualization of a view through a single lens. (Webb, 2014) Much like a telescope, this reference is both literal and metaphorical in nature, that allows for a visual understanding of the foveal cone. As an exercise, Webb deploys the notion that the air within the cone is solidified and thus, it can be removed from the overall landscape and investigated independently; akin to the ‘ice core’ concept mentioned within the discussion of the fovea. (Figure 05) As such, the cone becomes the site for Webb’s self-titled Journey that is used as a source of dialog for the investigative duration of the project. The work that develops within this thesis will co-opt concepts derived from Webb’s operation on the site, and moving forward, the simulations we use will each serve their own purpose as sites of discovery as we wade through the aliases and visions provided by their models. These sites, co-opted from the ideas presented by Webb, offer the simulations environments of serendipitous discovery. Step by step the simulations will explore the recurring loop of the perceptual process, starting with the landschaft, and exploring every facet of reconstruction and interpretation as the perceptual process unfolds.

Although the accompanying images as produced by Webb are mechanically constructed using well-established perspectival and orthographic drawing techniques, they simulate the vision of a single camera lens; only objects within the lens’ purview may be featured within the drawing.

(Figure 05) What lies behind the objects however, are negative ‘shadows’ that radiate from the camera lens. These spaces on the drawing share the same characteristics as shadows cast by objects obfuscating a light source, but in the case of Webb’s drawings, the vision of the lens is the source of datacapture. Webb describes these shadows as ‘voids slashing

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Figure No.05 Examples of the ‘ice core’ as a site, derived within the drawings of Michael Webb’s Temple Island project.

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through the ice-core sky, water and ground’. (Figure 06) Were the camera to be moved however, these voids would begin to rotate, and create new gashes within the surface of the cone. As an investigation, Webb proposes that, if one were to locate oneself within this ‘mobile caesurae’, it would present an ‘evanescent spatial experience’. (Webb 2014)

The term ‘mobile ceasure’, as used by Webb while describing the shadows within his drawing, can be described as the effect a light house would have in a bleak moonless night. The beam, or cone of light streaks across the environment, and the same inverted effect would take place within the shadow streaks that the objects within the regatta course would cast if one were to treat one’s cone of vision as a searchlight. The term ‘ceasure’ here can be related to music or poetry, as defined by the American Heritage Dictionary of the English Language, a ceasure is a “pause in a line of verse dictated by sense or natural speech rhythm”. Webb’s use of these two terms, a ‘mobile ceasure’, eloquently describes the pause or break in experience when viewing the site from these metaphorical ‘shadows’ cast by the lens of the camera, because the data collected by the view is paused due to obfuscation.

In conclusion, Webb questions the experience this drawing would provide given its existence, offering new insight into how the visual model of the site would evolve.

The nature of these introspective investigations will be what drive the serendipitous discovery throughout this thesis.

Figure No.06 Shadows cast within the ‘ice core’ of the regatta course. From Michael Webb.

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2.2 Scotoma

A scotoma (from the Greek ‘skótos’ or ‘darkness’) is an area of partial alteration in the field of vision consisting of partially diminished or entirely degenerated visual acuity.

(Cline et al., 1997) This area can be entirely or partially surrounded by a field of normal or relatively well preserved vision. (Figure 07, 08) The mechanical makeup of every mammal’s visual system includes some form of scotoma, due to the location of the optic disc. The optic disc is a small area of the eye where no photoreceptor cells exist, due to the optic nerve leaving the retina.

As noted in the work of ophthalmologist Donald Fletcher, what is important to understand is the scotoma’s relationship with the field of vision; there is no conscious awareness of visual scotomas, as they are simply regions of reduced information within the visual field. For example, rather than recognizing an incomplete image before the participant, participants report that objects within the visual field “disappear” on them. (Fletcher et al., 2012)

Whilst being a natural component to a healthy visual system, a scotoma can also be a symptom of damage to any different part of the visual system. This can be brought on by any number of different causes, most notably in the form of macular degeneration, brain damage, or exposure to severe light sources.

Also of note, the term scotoma is used figuratively in several other fields, not in relation to visual function, but the mind’s perception or cognition of the environment. In this work however, scotoma is deployed both metaphorically and particularly in the literal sense of the term, which succinctly lays out the foundation for our series of simulation exercises.

This connection, between the nervous system and the mind, originates through an ongoing dialog of sensory input, nerve conduction, and to the overarching architecture of the visual system. In the case of a human, the brain becomes the central organ that deals with all of the dialogue, and in the case of the simulations, all of these interlocking components described will be metaphorically simulated, as well as displayed.

As distinctly noted by British neurologist Oliver Sacks, the processing and interpretation of said input leads to perception, via the brain-mind correlation to psychological function. After an accident in Norway, Sacks lost all feeling in his left leg. This experience led to one of his seminal works,

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Figure No.07 From author, examples of still scintillating scotoma on digital media sketch.

Figure No.08 From author, enhanced section of area effected by scotoma. Areas that fall within the visual cone are slightly degraded despite full visual focus.

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A Leg to Stand On, where he documented the interaction between the brain and its relationship to the body and the environment it inhabits. There is always a partial inability to see some aspect of the occupied environment, both from a visual and perceptive standpoint. There exists (sometimes simultaneously) a mental inability to conceive of even the possibility of seeing that aspect, due to the cognitive schema that lacks any provision for it. (Sacks, 1986)

A very simple example of this ‘lack of schema’ could be described by the example of hemispatial neglect; a neuropsychological condition often observed when damage is sustained to one hemisphere of the brain, causing a deficit in attention to, and awareness of, a portion of the field of vision. (Unsworth, 2007) As an example, a stroke affecting the right lobe of the brain can result in neglect for the left side of the visual field. This leads to outright neglect of the left side of sensory space, regardless of the fact that the affected person can still physically turn their system left. Although the most obvious effects occur in the form of degenerated visual perception, neglect in other forms of perception can be found either alone or in combination with its visual component.

(Vallar, 1987)

There are a few seminal discussions and examples regarding the nature of hemispatial neglect. Simply illustrated, a patient experiencing hemispatial neglect will leave the entire left or right side of their plate full, yet still claim they are hungry for more food due to a psychological or physical degeneration in this system of the body. Another phenomena can be seen in a ‘reverse phantom limb’ concept, where the mind will not process certain parts of the body within the realm of what side is psychologically neglected. This fairly common phenomena has been thoroughly explored in Sacks’ seminal work A Leg to Stand On.

Hemispatial neglect not only affects present sensation, but memory and recall perception as well. (Farah, 2004) A participant experiencing hemispatial neglect may also, when asked to recall a memory of a certain object and then replicate it, may only draw half of the object. What may be important to note however, that the cause of perceptual reduction may be unclear. This may be due to the fact that there is a perceptive deficit of the memory (loss of spatial information of the memory). In contrast, the memory of the object’s entirety may be fully intact, but the presence of such memory may simply be ignored.

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The concept of memory deficit is a fickle matter when dealing with a simulation of the process itself, as observed through photogrammetrical exercises undergone in Simulation No. 3. One could argue that a simulated system has no memory, only capable of dealing with what is visible at present, and interpreting a model devoid of influence from previous models. On the other hand, a simulated version of memory can be argued to be ever-present, where the photogrammetric process relies extremely heavily on the memory of a previous site. This is to say, a site may not have been possible without the input of another sample, or previous memory of the simulation. The exercises within this work will aim to develop this discussion as one of many introspective exercises regarding the model-making process.

Simulations No. 2 and 3 thoroughly explore the layering of discovered data samples, and showcase how the memory of the simulation may be observed in relation from one site to another.

Discussing the varieties of hemispatial neglect may also prove to be a strong metaphor for the simulation process of perceptual serendipity, an activity found in all aspects of the four simulations presented within this work. Concepts revolving around the sampling of data are strongly distilled in the exploration of the system itself, allowing the observer to suggest points of contention between neglecting pieces of information or harbouring it entirely, as Simulation No. 2 explores through the discussion regarding filters and sampling.

The workshops of UC Berkley neuroscience professor Mark D’Esposito explore the fundamental fact that no single mechanism can account for hemispatial neglect’s wide variety of manifestations, and a vast array of impaired mechanisms are found within it. (D’Esposito, 2003) The complexity of attention in itself, which is only one of many mechanisms that may interact with one another, has generated a variety of competing explanations on the subject of assigning particular presentations of neglect.

Regardless of the difficulty to assign certain scenarios, one can still loosely describe unilateral neglect within four major overlapping variables; type, range, axis, and orientation. (Figure 09) All four of these groups refer mostly to the physical properties of the participant’s environment. For example, range would refer to objects close or far from the participant, whereas the axis is simply horizontal or vertical neglect, as well as every angle in between. Type, for instance,

Figure No.09 Illustrations by patients experiencing hemispatial neglect.

Typical examples of axis degradation as shown by the clock face, as well as range degradations shown by the lack of three-dimensional replication in the cube and house samples. (Right) Courtesy of the Journal of Neurology, Neurosurgery & Psychiatry.

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deals heavily with input and output. Input regards mainly with inattention to sensory stimuli, and can even occur within imagined stimuli such as imaginations or dreams. Conversely, output type deals heavily with motor function, and the ability to navigate through or use the contralesional (unaffected) side of the system. (Mesulam, 2000)

Most importantly to the work of this thesis however, would be the iplications of orientation. Hemispatial neglect itself may take the form of both allocentric and egocentric models, perhaps pertaining to certain aspects of various percepts, or entire spaces within the environment entirely.

(Beschin, 1997) The term unilateral, as described by the Oxford dictionary, deals directly with ‘occurring on, performed on, or affecting one side of the body or one of its parts’. (Oxford English Dictionary, 7th Edition, 2006) Used in part with hemispatial neglect, unilateral neglect simply describes the nature of the phenomena. For example, if the left side of a patient’s brain suffers from a stroke, the right side of the patient’s spatial tendencies/cognizance will show signs of deterioration or neglect. There are many discrete manifestations that deal with classic spatial and quite frankly architectural discussions of hemispatial neglect as well.

One very classic example is the “Left of What?” discussion surrounding orientation. (Beschin, 1997) The work of neuropsychologist Nicoletta Beschin questions the frame of reference these patients adopt while neglecting half of their visual or perceptual field. The answer surrounding such a discussion has proven extremely complex, but can be divided very broadly into two defining categories. These categories tend to compete from simulation to simulation during the sampling of data, whereas one deals with the shutdown of half of the entire field, while the other shuts down half of every object within that field. (Beschin et al., 1997) Such a distinction may provide insight when investigating certain simulated elements of the perceptual process.

What is extremely important to discuss however, are the various theories surrounding hemispatial neglect as a disorder of spatial attention, or spatial representation.

(Bradshaw, 1995) These sub-categorizations of orientational neglect provide a more fluid environment for the discussions that surround Simulations No.2 and No.3. Spatial attention is the process where objects in one location are chosen for processing over objects in various other locations. (D’Esposito, 2003) This definition would imply that hemispatial neglect in and of itself is more intentional, which is mostly due to the

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fact that the participant has an affinity to direct their attention to certain portions of the environment. (Mesulam, 2000) The theory itself suggests that neglect is seen as a disorder of attention and orientation caused by the disruption of the visual processor. Participants with this disorder will direct their movements and attention to the unaffected side of their purview, while neglecting other aspects of it, despite having preserved visual fields. The result of this combination is an increased sensitivity of visual performance in the unaffected side of the environment. (Brandt et al., 2012)

The visual processor here encompasses the various phenomena that the visual system uses to perceive incoming data. One of the most notable parts of the visual system that processes this information is the visual cortex, but it is important to keep the discussion open to other forms of perceptual data. In essence, there may be a multitude of other factors that contribute to the creation of a new cognitive model within Simulation No. 4, and one mustn’t narrow our metaphorical ‘vision’ while observing the entire set of simulations themselves.

Spatial representation however, is the way space is represented within the brain. This particular theory outlines the idea that the underlying cause of neglect is the inability to form representations of the space on the affected side of the environment. (D’Esposito, 2003) As a result, participants demonstrate a failure to describe the affected side of a holistically familiar environment, from any given point drawn from memory. For example, two well-cited studies have been used to demonstrate that neglect can operate as a component of spatial representation. Both, in varying degrees, pertain to the perception of architectural environments, as well as to the participant’s interaction with their memory and experience of architectural environments experienced in the past.

The first study, whose site is shown in Figure 10, draws evidence from Bisiach and Luzzatti’s study of the Piazza del Duomo in Milan. Their experiment showcases memoryrelated neglect of a familiar architectural environment as perceived by the user. Participants within the study who exhibit hemispatial neglect, and were also entirely familiar with the layout of the Piazza del Duomo square, were observed during this exercise. The participants were then asked to imagine themselves at specific vantage points within the square, without physically being present. As an exercise, they were then asked to describe varying landmarks around the square, such as architectural features, materials, shops, etc.

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Figure No.10 Photocrom print by Photoglob Zurich, between 1890 and 1900. Piazza del Duomo (Cathedral Square). Milan, Italy, ca. 1895

Figure No.11 Illustration describing the experience of a hemispatial neglect patient as a result of the study conducted in Milan. Courtesy of Daniela Ovadia.

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At each specific vantage point, the participants consistently described landmarks only on the right side, and exclusively neglected the left side of their representation.

The key factor to the study however, was that their multiple descriptions of different vantage points showcased the fact that the participants had knowledge and reserved spatial information of the entire square. Consequently, they could only identify the right side representation of each particular vantage point. (Figure 11) When the participants were asked to change vantage points so that the environmental information overlapped with the unaffected hemisphere, they were finally able to describe the details within the environment that they had previously neglected. (Bisiach, 1996)

The second seminal study, observed similar patterns found by comparing physical stimuli within the visual field to the resultant imaging processed in the brain. (Rode et al., 2010) A participant who was confirmed to have knowledge of the map of France in its entirety, was asked to name French towns on a physical map, as well as recall their mental image of it. The map was then rotated 180 degrees physically, which should also rotate itself as a mental image within the brain. As a result of this mental exercise, from memory the participant was only able to name eastern towns within the country at first, and could only name western ones after the 180 degree rotation. This was because the western portion of the map was now in the ‘Eastern’ (right) section of the mental environment or represented mental field after the rotation. This means that the actual neglect stayed consistent with the mental image.

However, with the physical copy of the map, the participant’s focus was forced to stay exclusively with the Eastern towns of France, regardless of physical orientation. Simply put, seeing is not simply a visual exercise. The sampling of information and data being transferred to the mind has a direct correlation to physical stimuli, which results in a change of the mental image of the object.

This particular study led researchers to believe that neglect for images drawn from memory may be disassociated from the neglect of stimuli generated from the extrapersonal environment. (D’Esposito, 2003) In this case, the participant showed no loss of memory, concluding that their neglect was a form of deteriorated spatial representation. To conclude, spatial representation here can be described as the reconstruction of spatial frames or mental schema. These schema showcase the relationships of objects that may be perceived, imagined or remembered, in correlation to the perceived subject. As a

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result of the ongoing understanding conducted by the overall system, these schema are organized and acted on by the participant. All of these characteristics are key to observing the development of new schema or cognitive models that are brought forth through Simulation No. 4. A very classic example of a degraded mental capacity trying to access these schema, as discussed earlier, is what is described as a scintillating scotoma. These particular scotoma occur from abnormal functions within the back of the brain, and not within the components of the optical system. (Freeman, 2006). This is mainly caused by a pattern of changes in the behavior of the nerves in the brain during a migraine. As a result, the spatial schema of the object degrades as the reconstruction of information within the brain attempts to discern the image observed by the ocular system.

In conclusion, these two proposed studies suggest that the concepts of scotoma and hemispatial neglect are seemingly ‘dark’ portions that exist both mentally and mechanically within the foveal cone. These pockets of visual acuity dissolve due to mechanical imperfections within the system, but are by no means cast aside to be literally neglected for the sake of Simulation No. 2 and No. 3, as their metaphorical and conceptual implications can be quite intriguing for the purpose of the work of the designer, as they move through the design process itself.

2.3 Periphery

Outside of the foveal cone lies the largest area of vision, described as the periphery. Peripheral vision, to its greatest extent, accounts for approximately 90% of the angular area covered by human vision. (Sardegna et al., 2004) Despite this, the acuity of peripheral vision is highly degenerated in comparison to the foveal cone, concerning itself more with orientation and location as opposed to the gathering of data related to detailed perception within the environment. As written by architectural designer Birgir Orn Jonsson, peripheral vision gathers stimuli to deal heavily with forming spatial hypothesis, as opposed to dealing with direct objects and detail. (Jonsson, 2014) As such, a very large portion of our visual field is dedicated to these hypotheses, yet modern representation, as well as our interaction with it, mainly addresses our central vision instead. (Figure 12)

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Figure No.12 Peripheral study done by Jonsson, taking care of scan data drawn from the periphery of view.

Peripheral vision is extremely weak in humans, and is severely hindered at distinguishing shape, colour, and detail. (Sardegna et al., 2004) As such, the serendipitous feedback loop within this thesis will aim to explore different expressive languages that interrogate the idea of peripheral representation, brought forth through the reconstruction process of perceptual data. Very similar to Jonsson’s Islands of Vision investigations, various simulated tools and modes of vision will aim to draw attention to the development of the periphery, aiding in the search for a redefinition of how the periphery is perceived. The scan, used as a new and inspired mode of vision, will offer a platform for the simulations to visualize the various ranges of the periphery. (Figure 13) As Jonsson’s work aims to have the participant witness themselves seeing, this thesis will allow the participant to witness the seeing unfold.

Figure 14 showcases an assembly of architectural attractors, obfuscators and scintillators in a choreographed relationship to the observer as they pass through the environment. (Jonsson, 2014) A few of these attractors skirt the edges of the participants vision, while others hide within the blind spots, constantly aiming to draw attention to the periphery. This new mode of seeing for Jonsson, allows the participant to dislocate themselves from the center of their gaze. It is a difficult task to interrogate a space that deals heavily with the periphery from our classic mode of representation; a mode that so often excludes it. However, the tools developed through Jonsson’s project catered to the dynamics of the visual field within the design process.

As such, the tools encouraged the juxtaposition of models at different scales according to their position in relation to the viewer. (Jonsson, 2014)

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Figure No.13 LiDAR scanning modelled by Jonsson, arranged according to fields of vision attracted by peripheral armatures. Digital collage above, physical model below.

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Figure No.14 Peripheral interventions by architectural designer Birgir Orn Jonsson. Above, physical model, below are the accompanied drawings.

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It is important to note that the periphery is also a very strong component for collecting visual data from the environment. It plays a much larger role than traditionally expected, as the act of perceiving the surrounding environment is an exercise of collecting data, most of which is impartial. In an interview with Dr. Rowe, a recently-retired optometrist in Ontario, he states his ongoing fascination with the implications of peripheral loss. As an example, a patient who, due to an accident, lost all visual acuity in the macula of one eye, which is the area of the eye that observes the foveal cone. The patient insisted on removing the eye in favour of a replica, under the impression that it was more or less useless for visual function. Dr. Rowe, knowing the implication of such an operation, was able to demonstrate to the patient how important this visual information was.

To illustrate, losing function in the macula simply removes the visual acuity of the foveal cone, but still leaves the ability to collect visual data from the periphery. When the uninjured eye was covered for a visual test in Dr. Rowe’s office, the patient focused on the ‘major’ loss of vision in the injured eye. Then, after swapping to obscure the injured eye, the visual difference is obviously quite stark to the patient.

However, after this simple test and including both eyes, the patient is able to understand the major peripheral loss when removing the bi-focal component to this particular part of the visual field. Peripheral vision as a tool for collecting visual data is often understated with regards to the entirety of the visual field, which is why some designers might choose to explore its relationship to perceiving space.

2.4 Perception

In essence, the visual field is described as the spatial array of visual sensations available to observation.

(Smythies, 1996) Generally, this definition is used as a basis for classic discussion surrounding the visual simulation of the environment. However, the overarching concept of the four simulations put forward within this thesis dig deeper into psychological discussions surrounding introspection, allowing the participant to view the process outside from their own experience. Within the realm of philosophy, the process of introspection relies exclusively on the observation of one’s own mental state, as described in the writings of University of Toronto professor William Seager within the Encyclopedia of Consciousness. Consequently, the idea closely relates to human self-reflection, which starkly contrasts to external observation - a very important component to the concept of

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observing all four simulations concurrently.

Introspection as a mental activity generally demands privileged access to one’s own mental state, unmediated by other (external) sources of knowledge. (Seager, 2009) This provides a unique and individual experience for each mental activity, allowing us to navigate any number of mental states.

These mental states may include any number of experiential phenomena, including sensory, cognitive, bodily, and so forth.

The ability to reflect on these phenomena is a key component to observing the languages that the allegorical simulations deploy.

“...why should we not calmly and patiently review our own thoughts, and thoroughly examine and see what these appearances in us really are?”

Plato, Theaetetus. (Translated by Benjamin Jowett for the MIT archives).

Introspection as a means of informing the observations of Simulations No. 1 through 4 becomes crucial to initial thoughts on a new language or ‘expression’ drawn from simulated perception. By deploying the technique of introspection, we can observe the ongoing role these expressive languages play within the process of design and understanding. Perception, by definition, is the organization, identification, and interpretation of sensory information in order to represent and understand the presented information, or the environment. (Schacter, 2011)

Developing off of Schacter’s definition of perception, the term represent and representation needs to be unpacked in order to maintain a clear understanding for the nature of the simulations presented within the thesis. The idea of representation can also be understood as ‘language’, in a sense that we are observing the discovery of new languages brought forth through the simulation exercises. Another synonym for the term represent within this body of work could be reconstruct, in the sense where we are observing the reconstruction of the simulation’s understanding of the environment. In essence, all perception involves signalling.

This signalling is an ongoing barrage of information that passes through a nervous system. (Goldstein, 2010) As an example, vision involves light striking the retina of the eye, but for the purposes of our allegory, the nervous system can become purely mechanical, allowing each aspect of all four simulations to give us access to a simulated ‘mental state’ for

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the participant to observe.

Perception is by no means simply the passive receipt of proximal stimulus, but it is also shaped by the individual’s cognitive models and model-making ability. At its core, perception can be dichotomized into two processes; the first, being the process of sensory input. This transforms low-level information to higher-level information for further use by the participant. An example could simply be extracting shape data for object recognition or referral. The second process however becomes much more referential. The process itself is directly connected to a person’s concepts or expectations (knowledge) and the selective mechanisms (attention) that influence the perception itself. (Bernstein, 2010) There are many psychological layers to the concept of perception, but in real time the act of perceiving seems subjectively effortless; it’s important to note that the processing happens outside of conscious awareness. (Goldstein, 2010) This is crucial to the recurring loop from Simulation No. 4 back into Simulation No. 1 due to the fact that we are consciously interacting with the processing stage itself, and actively making design or discovery-based decisions as the processing stage unfolds.

What is important to discuss are two fields of discourse in particular that will contribute to the dialogue of this study. On one hand, perceptual systems can be studied computationally, in terms of how the information is processed and the way that this processed information interacts with our cognitive models. Along a similar vein, the perceptual dialogue revolving around philosophical issues includes the extent to which sensory qualities exist in objective reality rather than solely with the mind of the perceiver. (Gregory, 1987) This is an important discussion with regards to simulating the perceptual process because the study of illusionary or ambiguous imagery has demonstrated that the brain’s perceptual systems actively and pre-consciously attempt to make sense of their input. (Gregory, 1987) As such, the perceptual systems of the brain enable the participant to see their environment (Umvelt) as stable, regardless of whether the sensory information is typically incomplete or rapidly varying.

From a computational perspective, the human brain is structured as a modular network, where different areas process different kinds of sensory information. What is important to discuss however, is that some of these modules take the form of sensory maps, mapping certain aspects of the environment across part of the brain’s surface. (Calvert,

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DeVere, 2010) As a result, these modules are interconnected and influence one another during the process of structuring the process of perception.

The process of perception, begins with an external object, known as the distal stimulus or distal object. (Goldstein, 2010) By means of a physical or simulated process, the object stimulates the sensory mechanisms, and transforms the input energy into neural activity. This process is known as transduction, with the raw neural activity being the proximal stimulus. (Pomerantz, 2003) The neural signals themselves are transmitted to the brain for mapping, and the resulting mental re-construction of the distal stimulus is what Goldstein describes as the percept.

As a brief example, (Figure 15) shows an image of a tree within a landscape. The tree itself is the distal stimulus.

When light rebounds from the tree and enters the optic receptor, the resulting stimulation would therefore be the proximal stimulus. Finally, the reconstructed image of the tree by the brain, or simulated counterpart, would be the percept.

Stimuli are not necessarily translated into a percept and rarely does a single stimulus translate into one percept specifically.

Figure No.15 Landscape of digital environment. Original model courtesy of Spanish PC modder under the moniker of ‘Unreal’. Bottom and right images edited by author including new percept for simulated study.

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An ambiguous distal stimulus (with varying degrees of ambiguity) may be translated into multiple percepts, experienced randomly, and exclusive of each other, in what is called multistable perception. This perceptual phenomena is described as a set of unpredictable sequences of spontaneous subjective changes. (Eagleman, 2001) A classic example of multistable perception at work would be the work of mathematical artist M.C. Escher. Due to the 2-D language of the representation of 3-D space, depth becomes more ambiguous to interpret depending on the various angles from which the image is viewed. Figure 16 shows an example of Escher’s work, entitled Waterfall, whereas Figure 17 shows a more modern, colourful rendition from the iOS game Monument Valley. Both show how the isometric angle of representation (as one perticular derivative) can be utilized to degrade the way the image is perceived.

Figure No.16 M.C. Escher, Waterfall. 1961 lithograph. Courtesy of mcescher.com.

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Figure No.17 Modern examples of imagery inspired by the work of M.C. Escher, found in the iOS game called Monument Valley. Multistable perception is used here not only as a visual style, but as a gameplay mechanic as well. Courtesy of ustwo.com.

Perceptual multistability can be evoked by visual patterns that are relatively ambiguous for the visual system to recognize with only one unique interpretation. As an example, the bottom half of Figure18 shows an object wrapped around a tree, which now becomes the percept within the simulation.

The form of the object is created in such a way that varying degrees of this ‘multistability’ may be experienced, due to classic design nuances that juxtapose the object within the environment, while also providing it cover within the fidelity of the image.

In stereo vision, such as the human sight, the object should be able to be discerned at various angles and depths, which fold to and from the participant. However, in monocular simulation (such as a photograph of the object) the elimination of depth perception causes multistable perception to take over, causing the folding object to invert certain depth values in the reconstruction. This example of an ambiguous figure demonstrates that a single stimulus can result in more than one percept, and the percept can bind sensations from multiple senses into a whole.

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Figure No.18 From author, multistable perception investigations using percept, physical model in digital collage.

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2.5 Visual Perception

The process of perception begins with an external object, known as the distal stimulus or distal object. For the purpose of the simulations, an external object is used as a catalyst to evoke instances of multistable perception. The object, or ‘distal stimulus’, is considered external with regards to the perceptual system it inhabits. The object is external insofar as its interaction with the environment. For example, the trees surrounding the object may also be considered external objects, as they are being perceived by the system as well. By means of physical or simulated process, the object stimulates the sensory mechanisms, and transforms the input energy into neural activity. The neural signals are transmitted to the brain for mapping, and the resulting mental re-construction of the distal stimulus is what is known as the percept.

The distal object shown in Figure19, is one of a few variations added for perceptive observation, also providing access to multiple sites through serendipitous discovery.

The following reconstructed versions of the percept, will become key components of dialog when observing the simulations. This discovery will come via multiple simulations and the layering of their digital secretion. The concept of high definition, and using fidelity as a cue, gives us access to what Sheil notes as a “theoretical assemblage of spatialised imaginings”. Through the assemblage of new aliases and percepts, we can step back and observe the process of perception.

As an object within the space, the distal object has relatively low depth, but interacts with the environment through shadow and reflection, sometimes blooming to a degree in which it blends in with the sky. (Figure17) As such, the minimal physicality or mass of the object starts to produce interpreted ‘symptoms’ in its reproduction. The tool which we are using has also rendered the object textureless, providing some views with obscene glare, and assigning the object a colour fairly foreign to its context. As an early simulation, we can discuss the idea of architectural representation in its traditional form of two-dimensional imagery, both perspectival and orthographic.

If we were to represent this object as it rests within the site traditionally, we would provide a series of two-dimensional images consisting of necessary orthographic views (plan, section, and elevation). This in turn generates a collection

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Figure No.19 From author, early distal object exercise. Bottom image shows a reconstruction after given hundreds of image data entries. The object begins to dissolve in some moments, and capture the environment in others.

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of imagery that attempts to foster our perception of the object in its entirety. With regards to this simulation exercise however, there simply isn’t enough information to simulate a complete perceptual experience. That is to say, ‘complete’ being our classical definition or ‘whole’ representation of the environment. This concept of insufficient information, while usually contrary in our classic understanding of perceiving space, become the valleys to our metaphorical peaks when making discoveries within our sites.

To explain in terms of computer graphics, a fullyrendered or reconstructed version of an environment goes through an anti-aliasing process. The anti-aliasing process itself generally ‘smoothens’ out any jagged imperfections in the reconstructed image, to provide a more ‘realistic’ representation of what is reconstructed. (Figure 20) In essence, the simulations of this thesis explore the ‘in-between space’ of these jagged reconstructions, referring to metaphorical valleys and peaks that are akin to a sine wave.

Figure 21 presents an early example of this concept put to work. A physical model (Figure 22) of the distal object resting on a blue quilt was digitized. The tool used to digitise the object was given 2-D information traditional to our understanding of classic representation and, as a result, only fragments of the object were re-constructed. Small islands of visual acuity are drawn out from the information provided to the simulation, and as a result of filling in the gaps, a new perceptual understanding of the object, or percept, may be gained.

The design of the actual object and its relationship within the fidelity of the environment however are crucial to observe within the process of re-cognition. As such, we begin to achieve observations in the realm of re-cognition through the act of re-conceptualization. These simulations act on rebuilding cognitive models, or preconceived notions of how the environment is perceived and interpreted. The notion of fidelity also plays a major part in the way we compose and illustrate our designs as an assemblage of perceptions. As Kate Davies writes, “images mediate our understanding of the world, conjuring powerfully convincing secondary narratives that can serve to reveal truth, obscure it, or reinvent it entirely.”

The images or ‘sites’ presented through the simulations, will become crucial interactions with the way we discuss their outcomes or aliases. As such, the sites will also provide fodder for the rebuilding of said cognitive models, in search of new discoveries within the perceptual process.

Figure No.20 The bottom image shows the aliasing applied to the above text. As illustrated, the aliasing process approximates and samples values to smoothen the ‘jaggy’ edges for a higher fidelity replication. Courtesy of re-vision.com.

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Figure No.21 From author, another distal object exercise done with a physical model, perched over a blue quilt.

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Visual perception, in its literal form, is the ability to interpret the surrounding environment using light within the visual spectrum. However, observing these simulations has already proven to give us access to not only new forms of visual language, but perhaps more so of a perceptual intuition. It is important to note that, in the case of the classic flea example through the work of German Biologist Jakob von Uexküll, the spectrum for perceptual intuition may not be referencing the visual spectrum. In the case of the flea, heat mapping plays a major role in the perception of the Umvelt for the flea. This will be explored in further detail during Simulation No 1.

There may also be insight available through the discussion of the two classic Greek schools of thought on perception, providing the first primitive explanations of how vision is carried out in particular to the human mechanical system. The first being ‘emission theory’, based on rays emanating from the visual system. An object was only seen due to these particular rays falling onto the object. A refracted image was seen from these rays, emanating from the eyes, these rays traversed the environment, and after refraction fell onto the object. (Hahm, 1978) From a purely mechanical standpoint, this may be akin to the way light reflects off objects in order to give the visual system of a human visual cues to reproduce the imagery within the brain. However, this may open up discussion to the philosophical question of if there’s a perceptual system to partake in the act of perception in the first place, then is there necessarily an environment to perceive to begin with. This touches heavily on the metaphorical topic regarding the serendipitous nature of the simulations, or more particularly, observing the unseen.

The second school of thought surrounding perception advocated for the so called ‘intro-mission’ approach which conceived of vision as coming from something entering the eyes, representative of the object. (Swenson, 2010) Both of these concepts (intro-mission and emission) relied on the principle that “like is only known by like”, a theory that has degraded since the time of Aristotle, but both purported that light was what made vision possible.

A more modern study of visual perception is often credited to Hermann von Helmholtz, following the earlier work of Leonardo da Vinci. Da Vinci’s examination of the human eye concluded that optically, the eye (from a mechanical perspective) was rather poor. As a result, the poor-quality information gathered from the eye seemed (at least to Helmholtz) that this alone would make vision impossible. This

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Figure No.22 From author, physical model orientation of ‘The Black Tree’ for initial perceptual simulations.

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would lead back to a more philosophical discussion regarding a concept that can be described as unconscious interference.

The main conclusion to Helmholtz’s work was that vision cold only b the result of some form of unconscious interference; a matter of making assumptions and conclusions from incomplete data, based on previous experiences. (Helmholtz, 1867) Inference therefore, would require prior experience of the world, or at the very least, some aspect of the models of which the world was comprised. The study of visual illusions has yielded much insight into what sort of assumptions the visual system may make, according to incomplete model data, or the improper usage of them.

2.6 Cognition

As defined by the Oxford English Dictionary, cognition is “the mental process of acquiring knowledge and understanding through thought, experience, and the senses”.

Human cognition is both conscious and unconscious, and draws upon a process that uses existing knowledge. However, the cognitive process also generates new knowledge or intuitive models for its own self-reference and for further use.

(Sternberg, 2009) Thus, cognition is typically described to be the act of processing information within the operator’s mind or brain. (Blomberg, 2011) As described by Sternberg, “cognition” normally refers to this processing of information, with regards to not only the mind, but the individual’s psychological functions. Most importantly, on an abstract level, cognitive and psychological systems can also operate on an artificial level.

The Latin verb cognosco, (form con ‘with’ and gnosco ‘know’) is a derivative from a Greek verb roughly translating from ‘I know, perceive’. In essence, the term translates from Latin meaning ‘to conceptualize’ or ‘to recognize’. (Franchini, 2011) This idea of recognition will be explored further within Simulation No. 1, discussing the recognition process. As a primer however, when the mind creates a generalization such as the concept of a tree, it extracts similarities from numerous recognized models. (Gluck, 2016) Generalization, as an exercise, is understood to directly involve the transfer of knowledge across multiple situations. (Walker, 2007) These situations, however different, are indefinitely tied to one another due to the constant referential nature that they have to one another. This is due to the cognitive process and the way the mind bridges these generalizations together.

However, Walker’s work outlines two branching

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theories of cognition that will be explored through the simulated systems. The concept of generalization is described by Walker as a system wherein humans recognize the similarities in knowledge acquired in one circumstance, allowing for the transfer of models of this knowledge onto new situated environments. However, the second theory involving this knowledge is what is described as ‘situated cognition’, which instead states that the user may apply past models in new situations and environments. In essence, this more or less outlines a ‘thinking on the fly’ model, where cognition simply cannot be separated from context.

To elaborate further, this could be due to the fact that the generalization stage is much more refined, wherein the observer is including their own models from past experiences, and replacing a new model that would undoubtedly become unique in conjunction with the current environment. It is this notion that is heavily explored within the serendipitous nature of the simulations, as we as viewers can observe the implantation of models that were previously unseen during the traditional, introspective process of perception.

Gestalt psychology, or the gestalt laws of organization are another point of discussion that encompasses the perceptual system. The principle outlines that when a perceptual system actively forms a percept (also known as a gestalt), the whole has a reality independent from the parts that compromise it. (Tuck, 2010) As noted by web designer and developer Michael Tuck, the rather famous phrase most commonly quoted from Gestalt psychologist Kurt Koffka, “The whole is other than the sum of its parts” is often translated incorrectly to greater than the sum. (Koffka, 1935) Koffka would always make the correction for people as it was not simply a principle of addition, as the whole has its own independent existence. (Heider, 1977)

This becomes extremely important within the study of perception, especially regarding Simulation No. 4. It is stipulated within the realm of Gestalt psychology that perceptions are products of complex interactions with multiple stimuli, but also maintains the concept that these perceptions aren’t merely responses to them. (Carlson, 2009).

There are a few properties that comprise a gestalt system, as previously discussed, multistability is one of them. the other three are emergence, reification, and invariance; all properties that can be found and analyzed throughout all four of the simulations within this thesis.

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Emergence, is most commonly portrayed by the image of the Dalmatian. (Figure 23) The image shown depicts a Dalmatian investigating the ground in the shade of nearby trees. The dog is not immediately recognized by identifying its parts, its tail, nose, feet or ears for example.

Instead, it appears as a whole, separate from the system it currently resides in. In a similar vein, the gestalt property of reification explores the constructive or generative component of perception.

All aspects of the Gestalt psychology of organization deal with one another in some aspect or another. Reification for example, deals with the generative aspect of perception.

Simply put, the experienced percept in this case contains more explicit spatial information than the original on which it is based. (Lehar, 2004) This concept is often studied and illustrated with the use of illusory contours, and engaging with the way the eye moves from one object to another.

These few examples of Gestalt organization are not necessarily seperable components to model individually, which is made abundantly apparent within our simulations, but they most certainly are different aspects of a single unified dynamic system. (Lehar, 2004) 3.0 SIGNAL PROCESSING 3.1 Pre-Aliasing (Sampling)

Within the realm of signal processing and data sampling, a reconstruction occurs when data is re-interpreted for a new format of understanding. Described as an alias, the Latin root of the term deals heavily within the realm of ‘time’, literally translating to ‘at another time’ or ‘otherwise’.

(Mitchell, Netravali). This concept of dealing and perceiving new aliases over the course of time plays a major role in which the designer develops their understanding with the environment and it’s users.

Simply put, a sample is a value or set of values at a point in time and/or space, parsed from an original signal.

In signal processing, sampling is the reduction of a continuous signal to a discrete signal as a by-product of the language differentiation between two points in the perceptual system.

This is most commonly seen as a transfer of data from the analog to the digital. Similarly, a sampler is a subsystem or operation that extracts samples from the continuous signal, a component to the process that can also be described as a filter.

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Figure No.23 Image of a Dalmation. A classic example when discussing emergence within the realm of Gestalt Theory. Digital.

Figure No.24 From author, physical model. Acrylic forms cast for signal processing samples.

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These two terms in particular, ‘sampling’ and ‘filtering’ offer differing connotations that are useful to explore, as understanding their definitions will open up insight into observing the simulation from multiple points of view. Figure 24 offers an example for this relationship, providing a physical model prepared for digitization. The material choice of the model was selected in hopes of generating a varied array of samples due to its ambiguous translucency and reflectivity.

An ideal sampler produces samples equivalent to the instantaneous value of the continuous signal at the desired points. In image generation through the sampling of this data, an alias is shown in conjunction with the original frequency, creating peaks and valleys in the metaphorical understanding of the environment. Anti-aliasing in this sense, would be the interpretation of the data between the samples in order to provide a closer-to-desired outcome that mimics the original frequencies that were initially sampled. As another graphical computing example, algorithms are used to smooth the `valleys` produced by the jagged reconstructions. This can be done in a variety of ways, but a very common example would be the super sampling of colour data within a single pixel of information, in order to average the transition from one object to another.

Drawing from the discussion that proceeds from observation, there is a process pre-aliasing that involves sampling the observed data in order to provide the simulation with language and content. Within the realm of computing or computer graphics, this is commonly described as prealiasing. There is, however, complete or partial suppression of certain aspects of the signal during this process, due to the culling involved with sampling the data. In a sense, samples may not be created, but simply made visible to the filters induced by the simulation. This begs the question; is the filter itself a passive or active mechanism within the simulated process?

The discussion surrounding hemispatial neglect makes its way into the sampling process, as it may be a conscious or unconscious decision to omit certain aspects of the original data. Figure 25 shows the result of multiple and rigorous digital scans of the model shown in Figure 24. The three different scans produce the texture maps shown, demonstrating variation in the filtering and sampling process regarding the same object. The texture maps are left untouched, as the file output provides a raw layout for the texture in preparation for the future combining of the scan

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Figure No.25 From author, three seperate digitizations of the acrylic-cast models prior.

Prioritization and layout determined by the scan and left untouched for representation.

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and the texture data within modelling software.

What is initially obvious is that, with heavy fragmentation of data, the object becomes more ambiguous to the sampling system itself due to a varying degree of ambiguity of the distal object. These points of data are culled, and either organized for larger bodies of sampling, or very meticulously laid out in a seemingly more organized format if no solution is found.

An object that is whole outside of the digital realm, becomes fragmented and disjointed due to missing information that begins with partial sampling of the original signal. For this exercise, a few questions arise as the discussion continues towards the idea of a filter. Let’s say, for instance, if one were to zoom in on one of the polygons in the digital reconstruction shown, this island of visual acuity would now become the site for new perceptual discovery.

How does the new design process relate to the data that was sampled prior? Is it simply being disregarded? In one sense no, because the sample is made visible by the perceptual process of the system, but in the example of the super-zoom, it’s completely disregarded in the sense of simply not being visible. Which begs the next question: if something simply isn’t visible, does it lose meaning with regards to the Landschaft? What even defines ‘visibility’, in the eye of the mind, and within the perceptual process?

Answers begin to surface as one works through the cognitive simulations provided by No. 2 and No. 3.

3.2 Filter

Providing a simple example of working through this concept, there are multiple comparisons made available to the features of the filter or sampler. These dichotomizations are, in no particular order: • • • • • • •

Linear/Non-linear Time-invariant/Time-variant Causal/Non-causal Analog/Digital Discrete-time/Continuous-time Passive/Active Infinite impulse response/Finite impulse response types of discrete or continuous-time signals.

As an example, two of the most important and overarching dichotomies on this list is between passive

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and active filters. Passive filters do not consume energy within the system, maintaining a very linear approach to data sampling for reconstruction. For example, these come in the form of high-pass or low-pass filters that split data during a line of transmission. Active filters however, play a much more involved roll within the system as their label suggests. A common example regarding analog systems would be a signal amplifier. Active filters offer more control and predicability for the reconstruction of certain perceptual systems, and in the case of reproductive error, active filters generally improve performance.

Another distinction to make here would be the difference between the time-variant and invariant capabilities of a filter, where the former samples data over a constant measure of time, compared to the variability and adaptivity within the time function for the latter.

Aliasing taps into many aspects of these different types of filters. However, the strongest correlation will be drawn from non-causal samples present within Simulation No. 4.

The concept of observing an inovative perceptual process and acting within this realm as a designer will incorporate ‘future’ samples, whereas a causal filter simply deals with past imputs and outputs.

For the simulations to follow, the organization of the various filtering processes will be discussed as new samples arise, and different expressive techniques are used. This in turn will expand the concept of the perceptual filter. The idea of a perceptual filter incorporates a seperate nuance from other, classical filtering techniques such as optical filtering.

Simply put, optical filtering involves a percept in the optical path that selectively transmits light of different wavelengths.

This is a major source of the data sampled within the visual system, perceiving two types of wavelengths, by using absorptive and interference (dichroic) filters. To compare, the perceptual filter that will be deployed throughout the four simulations will not only incorporate a simulation of the optical filtering system, but other methods of data capture as well, that will serve as an allegory for serendipitous discovery.

This in turn leads to investigations regarding the metaphorical eyes and the brain of these systems. The filter will also be explored from various different angles. For instance, is the filter left on its own to choose what is absorbed or reflected (speaking in classic optical terms), or is the filter a tool with set parameters? When the baseline is mapped within

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Simulation No. 1, the simulations to follow give birth to new serendipitous anomalies. The framework of Simulation No. 1 becomes an anomaly of the rules imposed from a previous perceptual system or engine, as no visual environment begins without some sort of inhabitation or expressive representation. The underlying question thus emerges: what becomes the value of these moments frozen and distilled?

The value here is drawn from the likes of Michael Webb’s ‘ice core’ investigations discussed earlier, they becomes sites for the allegorical simulations.

These answers will evolve over the course of observing the process and outcomes of the four simulations. The integral component to designer interaction with these simulations, as a perceptual interactive framework however (even when passive), will be the perceived data and the expressive outcome of the simulated language. Photographic filtering for example, is sometimes used to make subtle changes to images; on the other hand, the ontology of other images depends exclusively on the filter itself. Thus, the filter throughout the simulations will become an ontological machine, bringing artefacts into being. This will be brought about through the discoveries made based on the conceptual framework of ‘error’, and the layering of ‘erroneous’ data made visible by the simulations.

The filter may also be considered an environment within itself, a way for us to perceive and misperceive the world and it’s infinite Landschaft that we explore.

A multitude of questions are raised by the filter and the perceptual process moving forward. For instance, many of the filters that operate within all four Simulations will reveal new perceptual opportunities. The designer becomes integral to observing the meaning behind the emerging samples, and each oberver may have a different perspective on how powerful a role the filter will play within the layering of perceptual data. Ideas on the perceptual thought process, perceptual construction, and finally perceptual space will emerge after a rigerous loop of sampling. Regarding the scan in particular, the expressive rendering of sampled data will ultimately orchestrate a symphony of mobile ceasure in the words of Michael Webb.

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3.3 Aliasing

Simply put, spatial aliasing is accomplished through the reconstruction of sampled signals. In signal processing and related disciplines, aliasing is an effect that causes different signals to become indistinguishable (or aliases of one another) when sampled. It also refers to the distortion or artifact that results when the signal reconstructed from samples is different from the original continuous signal. Aliasing can be caused either by the sampling stage or the reconstruction stage; these may be distinguished by prealiasing and postaliasing.

Aliasing can occur in spatially sampled signals (as well as through time), and is most commonly explored through digitally rendered imagery. In essence, aliasing is digital imprecision generated in the process of converting analog information into digital space. This is mainly due to the level of granularity that digital reconstruction brings, and varys in degree depending on the type of system. When a digital image is viewed, a reconstruction is performed, partially through computation and output to a display, as well as through the eyes in conjunction with the brain. If the image data is not properly processed during sampling or reconstruction, the reconstructed image will differ from the digital image, and an alias is seen. An example of spatial aliasing would be the moiré pattern one can observe in a poorly pixelized image of a brick wall due to lack of proper display resolution. (Figure 26)

Figure No.26 Bottom image shows a poory down-sampled image of the above brick wall, resulting in a moire pattern being observed through the display. Courtesy of Colin M.L. Burnett.

There are multiple spatial anti-aliasing techniques that have been developed to reduce the impact of aliasing, especially within the realm of computer rendering and graphic technology. This sampling process in itself can occur pre and/ or post-aliasing, depending on the chosen method. In light of these technologies, the concept of anti-aliasing extends its meaning towards realising a higher graphic fidelity. The fidelity of the reconstruction however, will not be limited to post-aliasing with regards to the feedback loop of Simulations No. 1 through 4. This will be important moving forward during the topic of how graphic fidelity will be perceived both pre and post-aliasing, and will offer another metaphorical site within the gaps of interpreted samples. This concept of achieving a higher graphic fidelity however, will be explored first from the point of view of the simulation’s definition of ‘error’.

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3.4 Error

A digital artefact is any undesired alteration in data introduced in a digital process by an involved technique and/ or technology. (Merriam-Webster’s Collegiate Dictionary, 11th Edition, 2009) Similarly, an anomaly is a deviation from the common rule, type, or arrangement or form. An incongruity, or inconsistency; these are all terms that denote the driving force behind anti-aliasing technologies and techniques.

When creating digital artifacts during digital reconstruction for example, at what point do these alterations become undesirable, and at what cost? Can these alterations become harnessed?

The discussion of aliasing and the reconstruction of sampled data usually revolves around the concept of error, and even more so with error correction and undesirable outcome. The simple task of discussing error and its capability as a design catalyst will prove important as a metaphorical example of changing traditional concepts into serendipitous opportunities. Matthew Shaw’s The Surface Error Series, as part of his thesis work at UCL, (Shaw, 2010) compounds the slight errors implicit in the scanning process and shows the distortion, mistruth and beauty that repeated error can create.

A base SLS printed target is repeatedly scanned, 3-D printed and re-scanned for 12 iterations. This micro test of distortion could be applied on a city scale, thereby altering its digital appearance. (Figure 26)

Many conversions between continuous and discrete representations may occur in the course of generating an image. For example, when ray tracing a texture-mapped surface, a photograph may be sampled by a digitizer to define the texture, then the texture samples are interpolated and resampled when a ray strikes the textured surface. The ray samples are interpolated and resampled to generate pixel values, the pixels are interpolated for output to a display and finally resampled by retinal cells when the image is viewed. Resampling may be more explicit, as in enlarging or reducing a digital image or warping an image. Each of these conversions can introduce conspicuous errors into an image.

Ultimately, what needs to be defined is a new interpretation of an ‘error’. It is only an error insofar as it doesn’t completely replicate the analog. Moving forward throughout the simulations, the term ‘error’ in its traditional form will in a sense be abolished in favour of ‘a serendipitous discovery’, that may have its own influence on the next

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perceptual component to the simulated system.

Figure No.27 Presentation of scanned data by Matthew Shaw for the ‘Surface Error’ investigation. The project explores the same pannel scanned and re-scanned which accrues a buildup of data to garner a swathe of new sites for exploration. Courtesy of we-make-money-not-art.com.

3.5 Reconstruction

Reconstruction in itself, can most certainly be held responsible for particular forms of aliasing and other distortions that mar the subjective quality of an image. The key here is subjective quality, which relates back to the discussion of error. Quality, is most often associated with ‘good’ or ‘true’ recreations of an original signal, whilst error is mostly defined as an undesired outcome. Aliasing is almost always spoken of in terms of rectifying distortion due to the sampling process, but Simuations No. 1 to 4 will use these reconstructions as design drivers instead.

Reconstruction will be used as a descriptor for the amalgamation of error, a phenomena that in part is described

by Bob Sheil as ‘digital secretion’. (Sheil, 2014) The secretion of digital data and sampling will therefore be layered into multiple discoveries, in an attempt to discern new expressive languages and cognitive examples drawn out of the simulations.

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3.6 Digital Secretion

Digital secretion, a term used in the writings of Bob Sheil surrounding the discussion of high definition, is a concept that involves the continuous layering of data and information brought forward through emerging technological advancements. (Sheil, 2014) These advancements have been prevalent within the realm of architecture and design for multiple decades, but they still continue to provide innovative experiences and outlets that re-invent the way architectural data is perceived and visualized.

This concept, the layering of digital secretion, is a technique that is extensively used as a serendipitous and exploratory catalyst throughout the course of the four Simulations displayed within this thesis. The work of ScanLab, a London based firm born from the thesis work of Bartlett students Matthew Shaw and William Trossell, has been a very thorough source on the pioneering of this concept, as seen through their work regarding the LiDAR scanning of various landschaft.

Figures 28 and 29 showcase a sample of this work. various point cloud clusters are accumulated and collaged in a way that explores an unforseen visualization of certain areas of London. The technique shown within the firm’s work will be one that is conceptually co-opted within the four Simulations.

As a result, the layering of samples data can perform as a new expressive language for the continuous feedback framework that the simulations provide.

Figure No.28 Layered data clouds from a subway tunnel beneath the streets of London England. Digitally stitched together from various scans of the site by ScanLab Projects. Originally published on wire.com.

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Figure No.29 The above images are from the series entitled ‘Limbo’ by the design firm ScanLab. The images are a classic component to the work of the studio, in which collaging different data sets into an image provide a previously unforseen correlation (or sometimes even isolation) between different visions of architectural space. Courtesy of ScanLab Projects.

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Figure No.30 Landscape of digital environment.

Original image courtesey of Spanish PC modder ‘Unreal’. Image is focused on what will be the location of the percept for simulations 1 through 4.

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4.0 SIMULATION No. 1

Simulation No. 1 explores the concept of establishing an Umwelt for the simulations that succeed it. Loosely termed as ‘self-centered world’, cognitive philosophers theorised that organisms can have different umwelten, even though they share the same environment. Consequently, each functional component of an umwelt has a meaning and so represents the organism’s model of the world. The fidelity of our chosen umwelt will play a part in naturally degrading the field of vision, offering an interesting dialogue between the design of the percept and its relationship with how the simulation constructs its own umwelt.

4.1 Umwelt

The way we approach our main simulations involves a very inclusive set of definitions regarding our design and site work. Our environment for the sake of our theories refers to the digital engine that provides us our visual test-bed within which we work. There is however, a very simple way to dichotomize our definition between the environment, and how our simulations are taking part in viewing them.

Included in the semiotic theories of Jakob von Uexkull and Thomas Sebeok, umwelt (from the German Umwelt meaning environment or surroundings) is described as the “biological foundations that lie at the very epicenter of the study of both communication and signification in the human [and non-human] animal.” (Sebeok, 1976)(Stjernfelt, 2011) Usually loosely translated as “self-centered world”, Uexkull theorized that organisms can have different umwelten (plural) even though they share the same environment. At its essence, Uexkull’s examples provide us with fairly succinct definitions for how our simulated reconstruction of the environment holds value for us as an exploratory exercise.

Each functional component of an umwelt carries some sort of meaning, and in doing so, represents the organism’s model of the world. As described by Treisman, these functional components correspond to perceptual features.

The organism’s umwelt is also holistically semiotic to the organism, which is inclusive of all the meaningful aspects of the world for any particular organism involved. Most notably, this includes aspects of the world that interact with reference, navigation, and spatial awareness or understanding. The organism actively generates and re-constructs its own umwelt when it interacts with the environment it resides within.

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Termed, the ‘functional circle’, the construction and reconstruction of environmental elements differs for every organism, which follows from the uniqueness and individuality of every particular system. (Uexküll, 2017) The umwelt theory itself states that the world and the mind within it are inseparable, because without the mind interpreting the world for the organism, it simply wouldn’t exist. When two umwelten interact, they form what Russian scholar Yuri Lotman coins as a ‘semiosphere’. (Lotman, 2005) As such, worlds or environments can communicate with one another through semiosis - otherwise known as communication through signs and their interpretation.

By Uexküll’s definition, the umwelt also unites all semiotic processes of an organism into a holistic system, which confirms that there are multiple signifying processes from one part of the environment to another. In order to traverse the environment with enough understanding to function, the sum of these semiotic circles work together in a co-operative manner. This is what’s termed the ‘collective umvelt’, which models the system from a minute scale. What is key to note however, is that if any of these functioning circles depreciate, the organism will not operate in an efficient manner. This idea of efficiency is an external concept that will be explored within the simulations, as the observer’s concept of ‘efficiency’ may become contradictory to its classical definition whilst enduring serendipitous discovery.

Known academically as a renowned zoologist, the work of Jakob von Uexküll naturally draws upon biosemiotic examples to portray these systems. These examples deal heavily with animals or organisms and their relationship with their environments or umwelten. For Uexküll, the umwelt is an environment-world which is, according to Agamben, “constituted by a more or less broad series of elements [called] ‘carriers of significance’ or ‘marks’ which are the only things that interest the animal”. (Agamben) Paraphrasing an example of Uexküll’s work, Agamben uses the example of a tick and the three ‘marks’ of its environment;

“...this eyeless animal finds the way to her watchpoint [at the top of a tall blade of grass] with the help of only its skin’s general sensitivity to light. The approach of her prey becomes apparent to this blind and deaf bandit only through her sense of smell. The odor of butyric acid, which emanates from the sebaceous follicles of all mammals, works on the tick as a signal that causes her to abandon her post (on top

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of the blade of grass/bush) and fall blindly downward toward her prey. If she is fortunate enough to fall on something warm (which she perceives by means of an organ sensible to a precise temperature) then she has attained her prey, the warm-blooded animal, and thereafter needs only the help of her sense of touch to find the least hairy spot possible and embed herself up to her head in the cutaneous tissue of her prey. She can now slowly suck up a stream of warm blood.”

“In this particular example, the umwelt for the tick is reduced to three carriers of significance as expressed in chronological order, with the first being the odor of butyric acid, which emanates from certain follicles of all mammals. The second, would be the temperature of blood within the mamal, matching thirty-seven degrees centigrade (for the case of the tick’s prey). The last, would be the topography of mammals, which is unique in correspondence to hair follicles.” (Uexkull, 2010)

The conclusion here may at first be that (using the example of carrier two) the tick may enjoy the taste of blood, or that it possesses the ability to perceive its flavour or texture.

The work of Uexküll however confirms that this actually is not so, as laboratory tests show that it will eagerly absorb any type of liquid that matches thirty-seven degrees centigrade, which corresponds to the blood temperature of mammals.

(Agamben, 2013) The tick, in essence, lives only in this relationship as well as for it. Uexküll proposes, after removing the tick from its environment and into complete isolation, that “without a living subject, time cannot exist”. This begs the question of how it’s possible for a living organism, who lives entirely within its relationship to the environment, to survive in absolute depravation of it. As a result, Agamben asks what sense it would make to speak of this ‘waiting’ without time and without world. The connection and depravity of such connections to the environment will be explored as the simulations are used to discuss the questions brought forth from each correlating site.

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Figure 31 shows an example of how this concept is integrated into the simulations of perceptual awareness.

The scans produced by ScanLab for the New york Times investigate a world made visible by the self-driving automobile.

The scans, and the reconstructions produced, tap into a new language of vision only offered through this particular experiment. (Manaugh, 2015) The technique itself is one that will be commonly used within the serendipitous studies conducted through Simulations No. 1 to No. 4, as the scan is a very powerful armature for visual investigation. It will also serve as a stand-in system that will allow us as the observer to investigate the sites from an unbiased perspective.

Figure No.31 Images courtesy of ScanLab and the New York Times, constructed vision of a self-driving automobile. This scanning method aimed to portray a new mode of vision, previously unseen by pedestrians.

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In conclusion, the umwelt is a very important construct to provide us an initial test bed for the simulations. The various modes of vision used within the simulations will act as catalysts for discovery, weaving through the discussion pertaining to the fidelity of the umvelt both from a graphic and perceptual point of view.

4.2 Visual Fidelity

Fidelity as a discussion of visual accuracy is an important component to Simulation No. 1. High and low fidelity are terms used within the realm of signal reproduction, most notably used in the reproduction of sound and its related signals. High and low variations of fidelity, as defined by the Marriam-Webster dictionary, refer to the degree of how ‘accurate’ the reconstruction is compared to the original signal. The Latin etymology of ‘fidelity’ draws from ‘faithful’, attributing to the description of how ‘faithful’ the reproduction is. In general terms, the concept of fidelity deals heavily within the realm of what one perceives as an accurate representation of what the original signal may have been.

Fidelity is most notably used in terms of describing levels of visual acuity. The usage is also often blurred with or interchanged within the discussion of definition within a visual environment. We often use fidelity as a descriptor for how clear an environment is, and is an important component to the content of the simulated sites involved within this work. Figures 32 and 33 respectively show one of the first introductions of the distal object superimposed onto the selected area of the umwelt. Various digital reproductions and edits were made in order to slowly transition the object’s implementation into the site. This allows the viewer to discern what components of the umwelt are contributing to the evolution of the percept’s relationship with it.

The concept of the fidelity of the environment, as well as the composition of the images presented to the system as samples, will play a major role with its introduction for Simulation No. 1. As the allegorical simulations progress, the observer will discover the relationships between the aliasing induced through sample reconstruction, and how it’s effected by the umwelt itself.

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Figure No.32 From author. Physical model super-imposed on the possible environment. Specific tree was selected for this study due to its location bordering multiple environmental conditions.

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Figure No.33 From Author. Image views based on previous set, with image retouching done do enhance visual and graphic fidelity. Digital insertion of the photographed percept much more integrated into the image.

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Figure No.34 From Author. Image showcasing the blend of visual fidelity and serindipitous interaction when left to rest within the umwelt, as a result of the physics implemented by the digital tool.

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Figure No.35 From Author. Image showcasing the blend of visual fidelity and serindipitous interaction when left to rest within the umwelt, as a result of the physics implemented by the digital tool.

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4.3 Recognition

Recognition of the emerging cognitive models leads us into the development of the scan. Referred to here as armature for ‘seeing’, the scan offers a way to conceptualize spaces and forms in terms of saturation and density; very much akin to peripheral vision. This allows us to dismantle the dominance of privileged form and to focus on the notion of perception through simulated experience. Conceptually, this is perhaps more in tune with our spatial perception within the fidelity of natural environments or ‘Umwelten’, in which our focal points and lines of reference naturally degrade, in favour of heightened peripheral awareness.

Now, with regards to the discussion of fidelity, or most often pooled into the concept of ‘high definition’, this is where we can access the notion of an assemblage as Sheil previously discussed. By designing our distal object in such a way that it converses with the fidelity of the image, we can view its effect on how the environment is perceived its presence.

As an early investigation, Figure 36 shows a model of varied papercraft materials alongside translucent acrylic.

The models were produced through various techniques of scanning, including LiDAR, volumetric, and photogrammetric techniques. Each technique recognized and interpreted the same materials in a varied manner, opening up a serendipitous component to the visualization of the reconstructed language.

Moving forward, these techniques will all be utilized within the next two larger simulations, in order to capture various visual modes. The final image in the sequence, Figure 36 shows a layering of these data samples. This technique was introduced as a way of layering what professor Bob Sheil coins as ‘digital secretion’; a multilayering of data and aliases that will, for the purposes of our simulation, provide the work with various sites to investigate.

Overall, recognition will be the initiating characteristic of cognitive model-making. These cognitive models, derived from simulated perception, provide insight towards the sampling method and organizational characteristics of the reconstructive process itself. As such, the layering of these varied recognitions provide a development of aliases that will inform the findings of this introspective exercise.

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Figure No.36 From author. Different methods of ‘viewing’. Digital scans done with different techniques to study aliasing and nuances behind each one.

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5.0 SIMULATION No. 2

Simulation No. 2 constructs a narrative around the concept of simulated cognition. Various elements are probed in order to gain insight on the cognitive models developed during the initial stages of aliasing and construction.

Information in various forms are introduced to the system and therefore we can begin to observe how various percepts are being evaluated.

5.1 Reference

Reference as a visual activity is a very active portion of our model making capabilities. Reference plays a major role in the discussion surrounding the fidelity of the environmental scene. This plays into the layout of the various percepts within the environment, and how to anchor the viewer within it. Reference here is used as a baseline, or a site in which to begin the drilling or jamming process.

5.2 Drilling

‘Drilling’ is a term used heavily in the work of Bartlett Graduates Matthew Shaw and William Trossell. Their initial thesis work delved into the technology of LiDAR, or Light Detection and Ranging Technology. Their initial probe, LiDAR-jamming “stealth objects”, envisioning a future in which cities are subject to the constant scrutiny of LiDAR scans. (Shaw, Trossell, 2011) Shaw and Trossell devised hypothetical devices for deceiving the lasers and distorting what they recorded. A speculative tool called the “stealth drill” was meant to dissolve scan data, “creating voids and new openings in the scanned urban landscape.” A “boundary miscommunication device” would trick scans into registering paths, tunnels and walls that didn’t exist. (Figure 37)

These devices explore the city of London from stealth locations, “breeding” 3D scans with speculative LiDAR blooms, blockages, holes and drains. These reconstructions played a crucial role in understanding the way these devices perceived the city, and offered new insight into imagery that wasn’t present before the jamming took place. They were strategically deployed devices which offset, copy, paste, erase, and tangle LiDAR data around them, which allowed these drills to carve out new samples with an innovative mode of vision. The deployment of this “flash architecture” and toolpaths offered are what Shaw describes as a perceptive set of stealth mechanisms. (Shaw, Trossell, 2011)

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With regards to Simulation No. 2, the implementation of ‘stealth objects’ put forth by ScanLab has influenced the design and texture of the percept used. After observation, this distal stimulus provides the simulation with a probe to catalyze the cognitive jamming taking place in all aspects of data sampling and reconstruction. This without a doubt offers insight into the simulated organization of cognitive models, and the way the designed object interacts with them.

Figure No.37 LiDAR jamming device prototyped in wood. Courtesey of Matthew Shaw.

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5.3 Cognitive Jamming

Cognitive jamming is crucial to outline for Simulation No. 2 as it provides a ‘natural’ allegory for the way we can view our interaction with the site. The Black Tree exercise in previous investigations will serve as a cognitive drill for the remainder of the simulations, and illustrates the influence the drill has on the site. What is important to note is that it does not matter if the object is in frame or not; it operates as a drill for the landscape as shown within the work of Matthew shaw and William Trossel of ScanLab. (Shaw, Trossell, 2011) (Figure 38) The scan itself also becomes a component of the drill by representing the alias of an architectural object.

Understanding becomes experiential, an alias is drawn for the object and takes shape based on the imaging sequence.

In the case of the Black Tree, due to its thin, sharp form, it becomes hard to immediately interpret depth, existing almost as a shadow of the analog. This is perhaps why we are drawn to intricate, or even organic objects, as they are not readily grasped or understood even in full view.

Figure No.38 Scans as a result of LiDAR jamming, disorienting the language of the reconstruction induced by the various stealth jammers.

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What starts to become apparent however, is the amount of data that is necessary to achieve certain levels of reconstructed aliasing. Current forms of representation (i.e. orthogonal views) can provide only an inferior perception of an object, due to the sheer volume of samples needed to intensify the cognitive aliases. The sample in Figure 39 for example, solidifies the idea that perceiving an object is a massive undertaking of data transfer and sampling from an enormous pool of resources.

What is interesting to note is that we first need traditional forms of representation of the distal object for the program to create depth, context, light, shadow, etc. All of these things need to be present in order for the perceived object to even BEGIN to take form. Even after the introduction of traditional representation methods, the alias could not be drawn or recognized due to the lack of visual input data. What is evident is that it now becomes possible for the composition of the image to provide a reference point. Out-of-focus images with no contextual background won’t even be judged by the programs involved with the simulation, yet what is created from a pseudo-complete understanding is an alias, with some parts attempted based on incomplete and therefore misjudged data. Overall composition of missing data as a reference for reconstruction becomes a major component to the altering of sampled data.

Figure No.39 From author. Mesh generated by the Black Tree, chunks of the umvelt are baked into the structure of the object due to referential treatment during aliasing., only possible after adding hundreds of data entries for the object to be visible to the scan.

In conclusion, we come back to the concept of serendipitous discovery through analysis and critique of the simulation. Through serendipitous exploration, a conceptual tool is born; an alias-assist, or in the words of Matthew Shaw, a stealth drill. The ‘stealth drill’ presented by ScanLab provided a perfect tool for affecting the way the environmental data was sampled. In essence, Simulation No. 2 not only showcases that such an object (i.e the Black Tree) disrupts the sampling of the original signal, but also collates information of the surrounding context in order to reference the surrounding umwelt. The drill, in the case of our simulations, becomes a referential object that catalyses serendipitous discovery, allowing for bifurcations in the simulated perceptual process to allow us to critique the simulations themselves. It becomes a speculative tool meant to dissolve scan data, and mar the sampling process pre- and post-aliasing. Figures 40 and 41 show the beginnings of the results of this jamming in Simulation No. 2, and offer further insights into the varying degrees in which the reconstructed site is portraying the simulated perceptions.

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Figure No.40 From author. Various simulations and cognitive models observed throughout the simulated perceptual process. The various anomalies and phenomena will prove serendipitous in nature as data passes from site to site.

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Figure No.41 From author. Above, an image of various jammed components to the reconstruction of the umvelt through the eyes of the scan. The distal object interacts heavily with the mapping of what tie-point data is influencing the data that is sampled. Below shows a series of images, a small portion of hundreds take of the umvelt in order to provide sites for the perceptual simulation.

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Figure No.42 From author. Zoom-in of anthropomorphic point cloud. Physical model of the distal stimulus on blue quilt was digitized for point cloud and colour data sampling.

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6.0 SIMULATION No. 3

The third Simulation explores the concept of discovering new modes of vision, as well as putting them to use during the recognition stages of perceptual simulation. It is important to note that Simulations No. 2 and No. 3 overlap in various ways, as the feedback loop of perceptual reconstruction layers onto itself, embedding them into the modes of vision we explore here.

6.1 Seeing

Surrealist painter Rene Magritte is widely acknowledged for his commentary on the always-present gap between words and seeing, mainly stemming from their painting The Key to Dreams (1930). Seeing always comes before words, and evolves into a very complex system involving cognitive discovery. We never look at just one thing; we are always looking at the relation between things and ourselves. Our vision is continually active, continually moving, continually holding things in a circle around itself, constituting what is present to us as we are. (Berger, 1977)

Soon after we can see as an infant, we become aware that we can also be seen. The eye of the other combines with our own eye to make it fully credible that we are part of the visible world. (Berger, 1977) Every image embodies a way of seeing. Even a photograph. For photographs are not, as is often assumed, only a mechanical record. Every time we look at a photograph, we are aware, however slightly, of the photographer selecting that sight from an infinity of other possible sights. The photographer’s ‘way of seeing’ is reconstituted by his choice of subject. (Berger, 1977) Soviet film director Dziga Vertov eloquently describes this awareness as an existential exercise; Figure No.43 From surrealist painter Rene Magritte, The Key of Dreams plays on the commentary that there is always a culture of language present between words and seeing. Image courtesy of courses.washington. edu.

I’m an eye. A mechanical eye. I, the machine, show you a world the way only I can see it. I free myself for today and forever from human immobility. I’m in constant movement. I approach and pull away from objects, I creep under them. I move alongside a running horse’s mouth, I fall and rise with the falling and rising bodies. This is I, the machine, manoeuvring in the chaotic movements, recording one movement after another in the most complex combinations.

Freed from the boundaries of time and space, I coordinate any and all points of the universe, wherever I want them to be. My way leads towards the creation of a fresh

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perception of the world. Thus I explain in a new way the world unknown to you.

(Dziga Vertov, quoted by Judith Wechsler, in the Fall edition of Daedelus.)

In essence, what Vertov is describing is the concept that the visible, in continual flux, becomes fugitive. To further illustrate this concept, we can look to the ‘uniqueness’ of a painting. The uniqueness of every painting was once integral to the uniqueness of the place where it resided. Sometimes the painting was transportable, but it could never be seen in two places at the same time. When the camera reproduces a painting, it destroys the uniqueness of the image.

As a result its meaning changes. Or, more exactly, its meaning multiplies and fragments into many meanings.

(Berger, 1977) This is essentially illustrated by what happens when a painting is shown on a television screen. The painting enters each viewer’s house. There it is surrounded by its wallpaper, their furniture, their mementos. It enters the atmosphere of the family. It becomes their talking point. It lends its meaning to their meaning. In other words, the mechanical redistribution of the image diversifies its original meaning. The original of the reproduction; its first meaning is no longer to be found in what it says, but what it it has now become.

Consequently, a reproduction (as well as making its own references to the image of its original), becomes itself the reference point for other images. The meaning of an image is changed according to what one sees immediately beside it or what comes immediately after it. Such authority as it retains, is distributed over the whole context in which it appears. (Berger, 1977) This concept plays a very strong part in the way we view the site as well as the drill within the simulations, as one of our major modes of vision is now provided by ‘the scan’.

The scan provides the possibility of entirely new understandings and engagements with the complexities of context, form, behavior and volume that heretofore have been unattainable, crudely approximated or poorly grasped.

(Sheil, 2014) What is important to note within the context of similar technologies, is that the scan is often able to achieve a level of fidelity that approaches reality. The intangible has caught up with the tangible. The focal point for advanced

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Figure No.44 Above: From author, sketches and overlays of percept to be studied under the perceptual simulations. Initial concept of the design to interact with the fidelity of the environment. Below: Digital umvwelt test setting, providing a high-fidelity environment to conduct simulations within each dedicated site.

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technologies in architectural design has shifted from the outer edges of the virtual to a position of hybridity with the actual.

(Sheil, 2014) (Figure 44) The tool range has made a profound leap in definition and fidelity and, data samples are explored across conditions of fine-grain information. Engaging with the difference between what is simulated and what is perceived, the images born from our simulations provide us with congruent sites that offer a new cognitive perspective, born from the opposing end of the fidelity spectrum. That is, the spectrum in which fidelity considers to be an exact representation.

In 1928 Walter Benjamin stated that the limits of photography ‘cannot yet be predicted’. (Mellor, 1978) Everything to do with it at the time was still such a new process that even initial explorations yielded strikingly creative results. In his work he noted that technical expertise would obviously become the tool of the pioneer in the field. “The illiterates of the future will be the people who know nothing of photography rather than those who are ignorant of the art of writing.” (Mellor, citing Benjamin. 1978) The scan, as an armature for seeing, illustrates this concept in the context of our simulations. The concept of discovery driven by the fidelity of the tool and its environments become our observatory (site of exploration). As put by Kate Davies, “images mediate our understanding of the world, conjuring powerfully convincing secondary narratives that can serve to reveal truth, obscure it, or reinvent it entirely.” (Davies, 2014) This becomes the crux of our findings regarding the scan.

The scan itself is an inspiring mode of vision, as it focuses on everything, all at once, and on nothing in particular. Representation and abstraction; dealing less with human experience or the reality of the material in its rich heterogeneity and subjection to external forces. (Webb, 2014) (Figure 45) Instead, the scan offers a way to think about spaces and forms more in terms of saturation and density, similar to peripheral vision, which deals less with form than the fovea. Much like vision in the dense natural environment, where peripheral vision loses focal points and lines of reference. Fidelity becomes a cue for the filter and the way the composition interacts with the peripheral object as well.

Creating an object that could reference, or be referenced by the landschaft furthers the idea of an alias-assist, or an alias with an agenda. As a conceptual tool, the drill becomes a referential object-to-object or object-to-environment entity that also explores the idea of serendipitous emergence.

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The scan offers a vision that is void of natural prejudice or hierarchy of value. Our investigation however, is to dissect the site that is now offered to us, and view it from an unbiased perspective. Various scans of the same physical model portray the organization and partial filtration of the distal object, in a manner that is seemingly undefined and varied in multiple instances.

What can be drawn from here is that we can produce varying degrees of reconstructed fidelity based on the same simulation. Even though the model is seemingly based in ‘our reality’, one can argue that from an allegorical perspective it is not our own. There are forces at work (as discussed in prior sections), that offer us insight into new modes of vision.

Figure No.45 Images from the work of ScanLab, investigating the romanticism behind scanning as a mode of vision. Berlin.

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6.2 Photogrammetry

Simulation No. 3 begins to evolve at this point through another perceptual process, simulated in the form of photogrammetric scanning. Photogrammetry is the science of deriving measurements from photography, offering another layer to reconstruction provided by the concept of the scan. In essence, the simulation will use a collection of photographs to calculate geometry and depth, capturing and layering graphic fidelity. “Meticulous layering and accretion of material and meaning upon a long and extended conversation of time, space, motion, geometry and fabrication talks of high definition as a theoretical assemblage of spatialised imaginings.” (Sheil, 2014) Therefore, the concept of the drill is not about blending in, but about losing reference and about exploration. The importance in the alias may come from the depth of the scan, the shadow, or what becomes unseen.

The scan, as an armature for ‘seeing’ offers a way to conceptualize spaces and forms in terms of saturation and density, very much akin to the function of peripheral vision.

This allows us to dismantle the dominance of privileged form and to focus on the notion of perception through simulated experience. Conceptually, this is perhaps more in tune with our spatial perception within the fidelity of natural environments or ‘Umvelten’, in which our focal points and lines of reference naturally degrade, in favour of heightened peripheral awareness. Now, with regards to the discussion of fidelity, or most often pooled into the concept of ‘high definition’, this is where we can access the notion of an assemblage as Sheil previously discussed. By designing our distal object in such a way that it converses with the fidelity of the image, we can view its effect on how the environment is perceived.

Here we are introduced to the crux of most of our larger simulations; the photogrammetric scan. There are many mathematical and spatial methods of scanning that currently offer us access to a formerly unseen realm of perceptual experience, but for the purposes of this simulation however, a more metaphorical approach has been taken.

Photogrammetric scanning is a method that utilizes two dimensional data to generate spatial understanding and contextual depth; It captures data from our most traditional form of representation and filters it with accurate perceptual sampling, layer upon layer. Figure 46 shows a dense point cloud of over 7.6 million points of coloured data. As an inspiring mode of perceptual vision, one can now begin to

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Figure No.46 From author. Results of a photogrammetric scan of the Umvelt, providing a new language to perceive the environment.

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witness a form of spatial aliasing, akin to our sub-sampling and processing of experience with the composition of the image before us, the object itself begins to break down as certain aspects of its form are sampled and interpreted. In terms of experiential data, the object in its entirety is the focus of the dataset, even while still struggling with the stability of its reconstruction.

However, when the object is moved to the periphery of the data set, the aliasing process begins to dissolve the object entirely, displacing the foliage and shadows of the phantomobject. The data filter is now actively sampling what it defines as visible to the eyes of the mind. What is also interesting to understand is the access our simulations give us to its own cognitive model-making process, some of which would have gone undiscovered. Here we see tie points, indicating from a single image - what the simulation itself understood as important referential moments, while simultaneously conversing with other image data during the reconstruction process. (Figure 47)

The points in blue indicate environmental references that match those of another image from a different viewport, while the white points were simply cataloged for consideration.

As a result we can begin to break down our understanding of how the distal object or drill is effecting the way the new cognitive models are created.

This becomes an extremely important cue for image composition, as no perceptual experience is identical or static. Aliases and reconstructions of the architectural object become experiential and unique, offering different modes of perception. Akin to an assemblage of sketches, traditional methods of representation (involving depth, context, light, shadow, form), all need to be present in order for the perceived object to even begin to take form.

As Kate Davies writes, “the sketch becomes the initial ghost, more of a sense of feeling. The sketch is the closest we get to the fragility and beauty of an imaginative thought.�

(Davies, 2012) As such, our simulations and the images generated from their cognitive re-building process, offer us sites for our own sketches of discovery.

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Figure No.47 Tie-points displayed after the image culling occurs for the photogrammetric system.

From author.

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Figure No.48 Point cloud scans of the first iteration percept, accompanied by views from the photogrammetric build in blue.

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Figure No.49 From author. Point cloud scans of the second iteration percept, (black) accompanied by views from within the original Landschaft correlating to the angle views within the point cloud. These views are now considered their own umwelt for further investigations within the sites.

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Figure No.50 From author. Different photogrammetric approaches were taken in an attempt to understand the digital language of the simulation. Various techniques in image identification were fed as data samples for the system.

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6.3 Peripheral Reconstruction

Peripheral reconstruction will become the component through which various discoveries are made and then, further acted upon. We will be able to observe the simulated process of construction through the combination of the scan and the simulated information-gathering by the photogrammetric study.

As a very rudimentary example, Figure 51 shows a minor recreation of the visual field with the use of panoramic algorithms. The purpose of the simulation here is to see how the reconstruction is affected by our initial percept. Initially, we can see that the drill is ghosted in certain areas of the scene, offering us an initial insight on how certain aspects of the visual field are being interpreted by the simulation.

This could quite possibly be an example of initial cognitive jamming caused by the drill itself and if so, offering insight as to what cognitive components of the site are being related or referenced in the field of vision. These types of dialog between the site and the distal object provide very rigorous feedback for the simulated perceptual reconstructions.

Figure No.51 From author. Peripheral reconstruction of the distal object resting on the site, influencing the way that the data is captured and ghosted wit its surroundings.

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7.0 SIMULATION No. 4

The purpose of Simulation No. 4 is to culminate the exploration of various aspects of our simulated experiences to provide us with the system’s own cognitive model. Based on previous recognition models generated by the layering of simulations, we can begin to see the growth of a new model.

Certain conditions and outcomes can be examined within the site, providing us new insight into the way we can interpret a brand new perception.

7.1 Re-cognition

Figure 52 overlays two data sets that become important in the dissecting of how the original site is interpreted by the simulation. Point-cloud data is superimposed onto the re-introduced tie-point data and made visible by the photogrammetric exercise. Photogrammetric data, in itself, becomes a very insightful indication as to which parts of the scene are prioritized over others. This data indicates common points of interest that will be used in the reconstruction of the scene, and will eventually provide us a new cognitive model for our design.

Likewise, figure 53 shows the initial investigations regarding the weight these tie-points carry within the composition of the image itself. What needs to be restated, is that every image generated from the perceptual simulation gives rise to a new cognitive model that is available to participate within the realm of the designer.

Density within these topographical maps begin to linger around concentrated points on the site. As such, they provide insight as to the vision of the simulation, which is an important study to attempt to understand the rule-set that drives the sampling and filtering process.

Figure 54 showcases another type of visible cognition.

An anomoly is visible within the distal object that is only visible whilst traversing the digital umvelt. Serendipitous discoveries such as these provide further investigation towards the reasoning behind data bridging.

In conclusion, the cognitive models that were reconstructed by the allegorical simulations become sites or foundations for the re-cognicizing of the models themselves and, as designers, how one can interact with them as an observer.

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Figure No.52 From author. Tie-point and point cloud data overlay.

Figure No.53 Two sets of images comparing the tie-point constellations to the corresponding topographical investigations. Tie-point prioritization within the perceptual simulation is used as a sampler when discerning the relevancy of perticular points.

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Figure No.54 Images of a previously unforseen error in the construction of the distal object.

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7.2 Cognitive Model Making

“Cognition is the mental action or process of acquiring knowledge through thought, experience and the senses. At its basic level, cognition uses existing conceptual models while simultaneously generating new ones.�

(Oxford English Dictionary, 7th Edition, 2006)

The generation of new cognitive models to be viewed by the observer is where the serendipitous nature of the entire simulation series begins to exponentially expand. Figure 55 displays an example of this layering. New methods of investigation arise from the concept of a new model-making process, brought forth through the rigorous allegorical simulations.

Here, we are introduced to the concept of re-cognition through re-conceptualization. What were once images of a landschaft, are now very specific visualizations of various umwelten as sites to participate in the observation and investigation of re-cognicized models. From this information, we can begin to discern new models of vision and begin to ask certain questions as to why some elements of the umwelt are prioritized over others. There are very clear indicators,

Figure No.55 From author. Example of a perceived cognitive model derived from layering previous models provided by the simulation.

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visible to the model, that showcase how the visual fidelity of the scene draws the vision of the simulation to certain percepts for reconstruction.

However, the drill in this case however seems to avert the gaze of the simulation away from this particular site. The initial investigation begs a few questions as to how the drill plays a part within the fidelity of the umwelt. As an example, the object may appear to be too ambiguous for the filter to deem aspects of it sufficient for the recreation of the site, which may further cause layering and alteration of it within the simulation process.

With ambiguous percepts (in this case the drill), noticeable ‘explosions’ of point cloud density are made visible after interpretation. These densities contribute to an assigned map of the texture mesh, offering information into the ordering and relative system the simulation employs to correlate certain textures.

Figure 56 and 57 present another initial reaction of how cognitive model making, or the emerging cognitive models, serve as a site to engage with the simulation, or perhaps evolve the design based on serendipitous mappings. The topography mapping shows relationships between the density of tie-points (only one of the few cognitive processes we have begun to engage with). Visible within the new data sets, other landschaft are derived for discovery, each with their own interpretation of the percept. The potential number of sites therefore becomes infinite, and we can begin to view the cognitive sketches from many different perspectives. Figure 51 goes on to evolve the derivative nature of the new cognitive models that take form from the results of the simulations.

Ultimately, the models generated through the framework of these simulations, provide a massive amalgamation of thoughts and perceptual concepts that are now made available to investigative opportunities for the designer.

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Figure No.56 From author. Investigative drawing of tie-point weight speculation, providing a more three-dimensional approach to the foveal cone that protrudes from the site.

Figure No.57 From author. Further investigations regarding other data samples, ultimately rendering the amount of usable ‘sites’ infinite.

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Figure No.58 From author. Visual cones extracted from the landschaft. These cones serve as various sites for each simulation.

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Conclusion 8.0 Serendipitous Perception

In conclusion, the various discoveries observed throughout the course of this thesis have grown from an overall framework of serendipitous perception. To varying degrees of utility, a multitude of techniques and processes have sampled and filtered data in bifurcating instances, allowing the observer to view new methods of vision and visual language.

The layering of these moments, give way to new discoveries involving re-cognition of the perceptual environment and the percepts that inhabit them. The simulations presented within this thesis serve as allegory; a system of interconnected metaphors that extend from site to site and inform the way the designer might incorporate emerging modes of vision and ‘high’ definition into the perceptual design process. As a result, the emerging cognitive discoveries contribute to a more robust and vigorous methodology, one that overflows into the realm of the designer and the design process, so richly steeped in perceptive understanding.

Figure No.59 From author. An example of how the layering of these serendipitous discoveries could influence the way the designer interacts with the new cognitive investigations.

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Lexicon of Terms Serendipity: Definition of perceptual serendipity as adapted by author. In 1745, Horace Walpole coined the term ‘serendipity’ suggested by The Three Princes of Serendip, the title of a fairy tale in which the heroes “were always making discoveries, by accidents and sagacity, of things they were not in quest of.”

(Merton, Barber, 2006).

Introspection: In essence, introspection is the examination of one’s own feelings or conscious thoughts. (Schultz, 2012) The process itself relies exclusively on the observation of one’s own mental state, and can be closely related to selfreflection. (Seager, 2009) As noted by Seager, introspection gives us access to our own mental state, unmediated by other sources of knowledge in order to keep the experience itself unique to the individual. For thousands of years, introspection has been a subject of philosophical discussion, as asked by Plato, “ …why should we not calmly and patiently review our own thoughts, and thoroughly examine and see what these appearances in us really are?” (Perner, 2007) Simulation vs. simulation: The serendipitous discoveries made throughout the course of this thesis emerge from Simulations intended as an allegory for the perceptual process. The capitalization of the word indicates that the findings come from one of the four major Simulations that compose a more robust framework for the discoveries, and their relevance to the perceptual process itself. The non-capitalized use of the word indicates that the findings came from other simulations, conducted before or outside of the realm of the four major counterparts. These findings in part helped influence the building of the framework in which the four major Simulations inherently portray.

Alias (Aliasing): Within the realm of signal processing and data sampling, a reconstruction occurs when data is reinterpreted for a new format of understanding. As another key point of discussion, the Latin root of the term deals heavily within the realm of ‘time’, literally translating to ‘at another time’ or ‘otherwise’. (Mitchell, Netravali, 1988). This concept of dealing and perceiving new aliases over the course of time plays a major role in which the designer develops their understanding with the environment and it’s users.

Models (Model-making): Models are traditionally thought of as a representation of an original object or environment. Within the work of this thesis, ‘models’ or ‘model-making’ are terms

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used to describe a component of perceptual experience, or the idea of viewing developed cognition during the simulation process. One can consider the definition of these models as conceptual archetypes, as defined by the Merriam-Webster dictionary, archetypes are considered “an original pattern or model of which all things of the same type are representations or copies”. The simulations explored within the thesis in essence visualize a new language for understanding these cognitive archetypes. The Webster dictionary also provides a relevant variation on the definition of a model. As described, a model can be a “series of postulates, data, or inferences presented as mathematical representation of an entity,” also described as simulations. The simulations within the thesis do present exactly as such; series of data interpreted by the simulated experience, in order to gain access to new forms of perceptual language and cognition.

Allegorical Simulations: This thesis utilizes simulated processes in order to explore the concept of cognition, and how the user perceives their surroundings. These simulations however, extend their meaning outside of the simulated environment, and offer the viewer a site for serendipitous discovery. These discoveries offer insight to previously unexplored languages and interpretations that are not normally visible when observing the process as a direct participant. Allegory, by Oxford definition is composed of various Greek components and meanings to construct the word itself. From allegorein, meaning ‘to speak figuratively’ and allegoria, the composition of these terms stems from allos ‘other’, egorein or ‘to speak publicly’, and finally agora meaning ‘assembly’. In concert, these roots compose a definition that is historically rooted in theatre and literature, but a very potent interpretation of the Greek root form of allegory plays a strong role in the description of what the simulations of this thesis aim to interpret. Working in tandem, the simulations and the sites that they are based in, are participants that construct an extended interpretation of what the perceptual process is for any given participant.

Simulations: See above; Allegorical Simulations Foveal Cone: The foveal cone is the part of the field of vision in which, as described in terms of visual acuity, is where vision is considered to be one hundred percent clear. It is also described as the central field of vision, where most of the clear focus is maintained due to the direction of the view.

(Strasburger, 2011) The term ‘cone’ is used to identify the geometric shape that visually portrays the concept distilled from other parts of the field of vision. As further portrayed

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in the diagrams of Michael Webb, the cone in which his investigations take place is clearly visible in the drawings.

(Figure 03).

Dialog: Dialog is a term commonly used within this work to term the metaphorical ‘conversation’ between the sites of discovery. In the case of Webb’s work, the imagery derived from the foveal cone interacts with the conversation between perceiving the environment, and the environment derived from his studies. The usage of the term dialog is an important reference to its verbiage, defined by the Oxford English dictionary, it is described as the action of partaking in the conversation rather than simply viewing it. this becomes a major discussion in the latter works of the simulations, as the thesis explores putting the new cognitive models to work.

(Oxford English Dictionary, 7th Edition, 2006) Landschaft: The term Landschaft is a direct reference to the work of Michael Webb, whose work in projects like Temple Island (1987) and The Journey (2014) strongly influence the terminology and basis of the simulations presented within this thesis. The word landschaft is translated from German to English meaning ‘environment’. However, the environment as an actor within these simulations weighs much heavier than a simple surrounding, as the simulations extract information and perceptual data in many forms. The Landschaft for this thesis sits at the top of an understanding hierarchy where every simulation is derived.

The Scan: The scan is a tool that will be described in detail as the simulation process is outlined. In short, she scan provides entirely new understanding and engagement with the complexities of context, form, behavior and volume that heretofore have been unattainable, crudely approximated or poorly grasped. (Webb, 2014) As an armature for seeing, the scan will offer a new and inspiring mode of vision for discussing the language of emerging perceptual models that emerge from the simulations.

Percept: From mid 19th century, from the Latin perceptum or ‘something perceived’ is a derived past participle of percipere, which roughly translates to ‘seize, understand’ on the pattern of concept and conception. (Oxford English Dictionary, 7th Edition, 2006) In philosophy, the Oxford dictionary simply describes a percept as an object of perception, something that is perceived or allows for the act of perceiving to take place. Within the simulations of this thesis, the percept will mainly relate directly to a designed architectural object that

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will interact with the Landschaft to various degrees, and catalyse the new perceptual models being drawn from them.

Perception (Perceptual Process): Rice University’s department of psychology professor James Pomerantz applies two key terms to the definition of the perceptual process. First, the process of transduction is the stimulation an object or environment of objects has on sensory mechanisms, which is a key component for observing simulated activity. The second term, encompasses the raw neural activity being brought into the system, coined as the proximal stimulus. Again, what needs to be understood is the fact that most current definitions of the perceptual process seem to deal exclusively or initially with the visual component of the process. However, there is discussion to be had regarding the recall process the simulated perceptual system has on retrieving or creating its own models for a representational language. This particular aspect of the perceptual process will be explored extensively within the latter three simulations of this thesis, including the cognition and re-cognition phases of the study.

Cognitive Models: See above; Models (Model-making) Perceptual Filter: The perceptual filter is a concept that derives from the traditional definition of an analog or digital filter within the realm of signal processing. The allegorical simulations put forward within the work of this thesis offer aliasing and sampling methods that take the shape of a simulated perceptual process. This process, will be thoroughly explored with regards to how the filter itemizes and prioritizes data based on the distal objects present, as well as the umwelt that it interacts with.

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