How to prepare a perfect video abstract for your research paper? – Pubrica

HOW TO PREPARE A PERFECT VIDEO ABSTRACT FOR YOUR RESEARCH PAPER? An Academic presentation by Dr. Nancy Agnes, Head, Technical Operations, Pubrica Group: www.pubrica.com Email: sales@pubrica.com

Today's discussion In brief Introd uc tion Techniques For Observation Video Abstraction Video Abstraction Proposed For Observation Video submission guidelines Conclusion

In brief An article's abstract briefly describes a frequently used document to pre-select content relevant to the user.

The abstract and the document are written in the same medium, text. In the multimedia era, video abstractions might be used similarly: as brief extracts that convey the essence of a longer movie, with no interruption in the presenting medium.

However, the current state of the art for indexing and exploring huge video archives is to employ textual abstracts.

A video abstract is a series of moving pictures taken from a lengthier movie that is significantly shorter than the original yet retains the original's essential meaning.

Introduction WHAT IS A VIDEO ABSTRACT? The same copyright rules apply to video abstracts to the corresponding article. The Video Abstract determines to emphasize the most critical aspects of your research.

Your focus should be on strategies to resentment your audience's interest and persuade them to read your work. As you will see in these recommendations, high-quality videos m a y be m a d e for a reasonable price.

IMPORTANCE OF VIDEO ABSTRACTS A technique for creating a video summary, which can be a sequence of fixed pictures (keyframes) or moving images, is known as video abstraction (video skims).

In terms of browsing and direction-finding, a good video abstract will allow the user to obtain the most information about the target video sequence in the shortest amount of time or enough information in the shortest amount of time.

Va rious

c oncep ts a nd a p p roa ches for successful vid eo

content abstraction have been presented throughout the years.

Here it describes the fundamental components of each method and how they are addressed in individual works.

Techniques For Ob ser v ati o n Video A b s t r a c t i o n Colour-Based Techniques - Because of its insensitivity and stability against changes in direction and size, the colour is the most effective, expressive, frame/image.

and

essential

Many video abstraction approaches according to this characteristic.

characteristic

of

each

exploited this feature

The colour histogram has been frequently utilized to produce abstracted video by calculating the similarity between frames to choose representative keyframes.

Animations - It might become difficult to convey some working principles or occurrences with manual sketching abilities over time.

You can use publicly accessible animation software tools to create dynamic or stationary picture graphics in such cases.

Unambiguous and straightforward representations are possible using programmes like Animaker, Blender, K-3D, and Plastic A nimation Paper, and these are more aesthetically attractive and a more cost-effective method to communicate your work in a captivating way.

PowerPoint

Presentation

-

Researchers

have

been

using

PowerPoint to showcase their findings on various platforms for a long time. This easy method m a y also be utilized to describe your study abstract utilizing PowerPoint's insightful pictures.

It's also free to use and comes with all of the tools you'll need to arrange your video abstractions with the help of clean slides. It's more crucial to focus on the section than the facts of your study while creating a narrative PowerPoint presentation for your video abstract.

Event-Based Video Abstraction identifies and arranges important events ( a t the highest semantic level) to preserve the original film's spirit. An approach that combines motion analysis with video skimming to create an event-based method examines the optical flow to find exciting events and compare them to previous data.

If no events of interest were detected, continuous frame dropping was employed, and those frames that featured events of interest were kept in the video abstract.

Combination types- The other approach for segmenting and classifying video segments used a mix of object and camera movements. The motion metrics are calculated using two optical flow algorithms, each employing two different keyframe selection criteria.

The quality of this procedure is that it can create meaningful abstracts for sports videos by collecting high activity material and being threshold-independent, but it is a domain-specific approach.

Video A b s t r a c t i o n Proposed For Obse r v ati o n Most video abstractions for research were created as browsing tools to make big videos easier to view and explore. On the other hand, video abstraction m a y be used as a preprocessing stage in video indexing and retrieval applications.

The first stage in video analysis is pre-sampling, which picks appropriate frames for subsequent processing an d minimizes the computing load. Incorrect sample rate results in a b a d video abstract ( lo w sampling ra te ) or a video abstract that is too brief (hi gh sampling rate).

The second stage in the video analysis module is feature extraction.

Feature selection and extraction are crucial processes that directly im pac t the clustering algorithm's effectiveness. Feature selection picks prominent characteristics, simple enough, and quickly computed features that characterize unstructured data. In contrast, feature extraction converts this input da t a from a highdimensional space to a lower-dimensional one.

Colour and texture are two critical aspects of any image's visual substance. Typical colour feature extraction approaches include colour histograms, colour moments, colour correlation, scalable colour descriptor (SCD), and colour structure descriptor (CSD).

They have computed a colour histogram in HSV colour space to extract colour features (which is close to hum an visualization). The computed histogram was then quantized to 8 bins to reduce dimensionality without sacrificing information ( 3 ) .

Technical Specifications when C reating a video abstract, video, and audio quality is critical. Making a compromise on one of these will defeat producing a multimedia abstract.

Ma ke sure your vid eo is record ed in a q uiet environm ent with no background noises.

Record your voice with a high-quality microphone.

Rec ord the a b stra ct in a well- lit room to p reserve a n excellent visual of it.

If not necessary, avoid using flash photography or videography.

Sep a ra te the na rra tion from the vid eo clip if p ossib le, a nd this will assist you in successfully managing your video's audio quality.

Accessibility- It's critical to save your movie in a format that academics all around the world can understand.

Video formats such as MP4, MOV, WMV, and MKV are ideal since they are widely used and compatible with most operating systems.

Maintain an appropriate aspect ratio to a c c o m m o d a t e all screen sizes.

Video s u b m i s s i o n g u i d e l i n e s The author should include video picture files as supplementary electronic material (ESM). When the manuscript is approved, an associate editor in charge of video submissions will ask the author to upload video pictures to MOMO (Make Our Movies Open) (through the website) and e - m a i l the rest of the manuscript to the associate editor.

On this occasion, instructions for the uploading procedure will be supplied.

The video cannot be changed or withdrawn once published in the Online First article. We propose that writers upload a new file to MOMO and get a different identification code if they want to change the clip for any reason.

If you have any questions, please contact the head editor. Please remember that we do not allow any films depicting h uma n conduct.

C on cl u si o n Many video applications rely on video abstraction, such as indexing, browsing, and retrieval.

The size of the keyframe set, representation scope, base unit, and underlying computational processes are all critical factors in keyframe extraction. Similarly, five key aspects are identified and explained for video skims the overall procedure, the duration of the video skim, the working d at a domain, the underlying calculation method, and the characteristics employed

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