TOP CITED ARTICLES IN COMPUTER GRAPHICS AND ANIMATION INTERNATIONAL JOURNAL OF COMPUTER GRAPHICS & ANIMATION (IJCGA) ISSN: 2231 - 3281(Online); 2231 - 3591 (print) http://airccse.org/journal/ijcga/index.html
CHILD EDUCATION THROUGH ANIMATION:AN EXPERIMENTAL STUDY Ashish Shingade and Archana Ghotkar, Pune Institute of Computer Technology, India
ABSTRACT Markerless motion capture is an active research in 3D virtualization. In proposed work we presented a system for markerless motion capture for 3D human character animation, paper presents a survey on motion and skeleton tracking techniques which are developed or are under development. The paper proposed a method to transform the motion of a performer to a 3D human character (model), the 3D human character performs similar movements as that of a performer in real time. In the proposed work, human model data will be captured by Kinect camera, processed data will be applied on 3D human model for animation. 3D human model is created using open source software (MakeHuman). Anticipated dataset for sport activity is considered as input which can be applied to any HCI application. KEYWORDS Animation, Blended learning, Education, ICT, Multimedia, Visual learning FOR MORE DETAILS: http://airccse.org/journal/ijcga/papers/4114ijcga03.pdf VOLUME LINK: http://airccse.org/journal/ijcga/vol4.html
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[12] Bernier, Olivier, Pascal Cheung-Mon-Chan, and Arnaud Bouguet. "Fast nonparametric belief propagation for real-time stereo articulated body tracking." Computer Vision and Image Understanding 113.1 (2009): 29-47. [13] Zhu, Rong, and Zhaoying Zhou. "A real-time articulated human motion tracking using tri-axis inertial/magnetic sensors package." Neural Systems and Rehabilitation Engineering, IEEE Transactions on 12.2 (2004): 295-302. [14] Lee, Mun Wai, and Ramakant Nevatia. "Human pose tracking in monocular sequence using multilevel structured models." Pattern Analysis and Machine Intelligence, IEEE Transactions on 31.1 (2009): 27-38. [15] Peursum, Patrick, Svetha Venkatesh, and Geoff West. "A study on smoothing for particle-filtered 3d human body tracking." International Journal of Computer Vision 87.1-2 (2010): 53-74. [16] Caillette, Fabrice, Aphrodite Galata, and Toby Howard. "Real-time 3-D human body tracking using learnt models of behaviour." Computer Vision and Image Understanding 109.2 (2008): 112-125. [17] Tong, Jing, et al. "Scanning 3d full human bodies using kinects." Visualization and Computer Graphics, IEEE Transactions on 18.4 (2012): 643-650. [18] Chanjira Sinthanayothin, Nonlapas Wongwaen, Wisarut Bholsithi. Skeleton Tracking using Kinect Sensor & Displaying in 3D Virtual Scene. International Journal of Advancements in Computing Technology. IJACT: International Journal of Advancements in Computing Technology, Vol. 4, No. 11, pp. 213 - 223, 2012. [19] Karina Hadad de Souza, Rosilane Ribeiro da Mota. Motion Capture by inect. SBC - roceedings of SB ames, X SB ames – Bras lia – DF – Brazil, November 2nd - 4th, 2012. [20] Zhang, Quanshi, et al. "Unsupervised skeleton extraction and motion capture from 3D deformable matching." Neurocomputing 100 (2013): 170-182. [21] Shum, Hubert, and Edmond SL Ho. "Real-time physical modelling of character movements with microsoft kinect." Proceedings of the 18th ACM symposium on Virtual reality software and technology. ACM, 2012. [22] Ilya Baran and Jovan Popovi´c. Automatic rigging and animation of 3d characters. In ACM S RA H 2007 papers, S RA H ’07, New York, NY, USA, 2007. ACM. [23] PrimeSense Ltd., Willow Garage, Side-Kick Ltd., ASUS Inc., AppSide Ltd. OpenNITM: Introducing OpenNI, http://www.openni.org/, 2010. [24] Microsoft Inc. Kinect for Windows: http://www.microsoft.com/enus/kinectforwindows/develop/, 2012.
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[25] The OpenKinect Community. OpenKinect (libfreenect), http://openkinect.org/wiki/Main_Page, 2011. [26] Code Laboratories Inc. CL NUI Platform - Kinect Preview, http://codelaboratories.com/nui/, 2010. [27] WIN&I Team; Evoluce AG., INCREON GmbH. Evoluce SDK, http://www.evoluce.com/_winandi/en/software/overview/index.php?we_objectID=55, 2011. [28] Delicode Ltd., NI Mate. http://www.ni-mate.com/ni-mate-v1-18-released/, 2013. [29] MakeHuman. http://www.makehuman.org/
CHILD EDUCATION THROUGH ANIMATION:AN EXPERIMENTAL STUDY Md. Baharul Islam1 , Arif Ahmed2 , Md. Kabirul Islam2 and Abu Kalam Shamsuddin ABSTRACT Teachers have tried to teach their students by introducing text books along with verbal instructions in traditional education system. However, teaching and learning methods could be changed for developing Information and Communication Technology (ICT). It's time to adapt students with interactive learning system so that they can improve their learning, catching, and memorizing capabilities. It is indispensable to create high quality and realistic leaning environment for students. Visual learning can be easier to understand and deal with their learning. We developed visual learning materials (an overview of solar system) in the form of video for students of primary level using different multimedia application tools. The objective of this paper is to examine the impact of student’s abilities to acquire new knowledge or skills through visual learning materials and blended leaning that is integration of visual learning materials with teacher’s instructions. We visited a primary school in Dhaka city for this study and conducted teaching with three different groups of students (i) teacher taught students by traditional system on same materials and marked level of student’s ability to adapt by a set of questions (ii) another group was taught with only visual learning material and assessment was done with 15 questionnaires, (iii) the third group was taught with the video of solar system combined with teacher’s instructions and assessed with the same questionnaires. This integration of visual materials (solar system) with verbal instructions is a blended approach of learning. The interactive blended approach greatly promoted students ability of acquisition of knowledge and skills. Students response and perception were very positive towards the blended technique than the other two methods. This interactive blending leaning system may be an appropriate method especially for school children. KEYWORDS Animation, Blended learning, Education, ICT, Multimedia, Visual learning FOR MORE DETAILS: http://airccse.org/journal/ijcga/papers/4414ijcga04.pdf VOLUME LINK: http://airccse.org/journal/ijcga/vol4.html
REFERENCES [1] Y. Roger, H. Sharp and J. Preece, (2011) “Interaction Design: Beyond Human-Computer interaction” John Wiley & Sons, Inc. [2] Toles, James LaFayette, (2009) "The Virtual Classroom: An Enhancement or Replacement to Traditional Education?", Undergraduate Research Awards, Paper 3 [3] Annual Report (2003) Department for Education and Skills and Office for Standards in Education, Departmental Report, http://dera.ioe.ac.uk/16365/7/CM%205402.pdf [4] Shafqat Hameed, Atta Badii, Andrea J Cullen, Effective E-Learning Integration with Traditional Learning in a Blended Learning Environment, (2008) European and Mediterranean Conference on Information Systems 2008 (EMCIS2008), May 25-26, Al Bustan Rotana Hotel, Dubai [5] Martin oliver, Keith trigwell (2005) Can ‘Blended Learning’ Be Redeemed? Journal of E–Learning, Volume 2, Number 1, pp. 17-26. [6] S. Nusir, I. Alsmadi, M. Al- kabi, and F. Shardqah, (2011) “Designing an Interactive Multimedia Learning System for the Children of Primary Schools in Jordan”, IEEE Global Engineering Education Conference (EDUCON), April 4-6, Amman, Jordan. International Journal of Computer Graphics & Animation (IJCGA) Vol.4, No.4, October 2014 50 [7] R. Shis, C. Papa, M. Chang, and T. Hsin, (2012), “Effect of Incorporating Project-Based Learning into the Development of an English Short Play for Children”, IEEE fourth International Conference on Digital Game and Intelligent Toy Enhanced Learning (DIGITEL), March 27-30, Takamatsu. [8] N. Kittidachanupap, J. Singthongchai, E. Naenudorn and N. Khopolklang, (2012) “Development of animation media for learning English vocabulary for children”, IEEE International Conference on Computer Science and Automation Engineering, May 25-27, Zhangjiajie, China. [9] Z. Muda, (2006) “Storytelling Approach in Multimedia Courseware: An Introduction to Science for Preschool Education, Conference on Information and Communication Technologies (ICTTA), vol. 2, Location (N/A). [10] Y. Chen, R. Yong, and L. Li, (2010) “Interaction design of children's mobile phone for enhancing cognitive ability”, Sixth International Conference on Natural Computation (ICNC), vol. 4, Aug. 10- 12, 2010 [11 Islam, M. Baharul, Islam, M. Kabirul, Ahmed, Arif & Shamsuddin, A. Kalam, (2013), “Interactive Digital Learning Materials for Kindergarten Students in Bangladesh”, Proceedings of 2nd International Conference of System Modeling and Advancement of Research Trends (2nd SMART 2013), 15-16 November 2013, Teerthankar Mohaveer University, India.
[12] Lukman, R., & Krajnc, M. (2012). Exploring Non-traditional Learning Methods in Virtual and Realworld Environments. Educational Technology & Society, vol. 15, no. 1, 237–247. [13] Alonso Díaz, L., & Blázquez Entonado, F. (2009). Are the Functions of Teachers in e-Learning and Face-to-Face Learning Environments Really Different? Educational Technology & Society, 12 (4), 331– 343. [14] Ahmed M. Al-Hassan (2010), A comparison of e-learning and Traditional classroom Teaching: Petra University, Conference of IATEFL [15] Shahinshah Babar Khan & Nabi Bux Jumani (2012), e-Learning versus Traditional Learning in Pakistan, Asian Journal of Distance Education, vol 10, no 1, pp 28 – 34 [16] Center for the Child Care Workforce (2007) EC E-Learning: A National Review of Early Childhood Education Distance Learning Programs. Center for the Child Care Workforce: Washington, D.C. [17] Sue Franklin, Mary Peat & Alison Lewis (2006) virtual versus traditional dissections in enhancing learning: a student perspective, Annual Conference Australian Society for Computers Assisted Learning in Tertiary Education (ASCILITE 2002), pp. 61-64, Melbourne, Australia. [18 ]Naser-Nick Manochehr (2006), The Influence of Learning Styles on Learners in E-Learning Environments: An Empirical Study, CHEER Volume 18, pp. 10-14. [19] Jorge G. Ruiz, Michael J. Mintzer, and Rosanne M. Leipzig, (2006), The Impact of E-Learning in Medical Education, Academic Medicine, Vol. 81, No. 3 , pp. 207-212 [20] Peter W. Stonebraker and James E. Hazeltine (2004), Virtual learning effectiveness: An examination of the process, The Learning Organization, Vol. 11, No. 3, pp. 209-225, Emerald Group Publishing Limited, www.emeraldinsight.com/researchregister [21] N. C. Premawardhena, (2012) “Introducing computer aided language learning to Sri Lankan schools: Challenges and perspectives”, 15th International Conference on Interactive Collaborative Learning (ICL), Sept. 26-28, Location (N/A). [22] Islam, M. Baharul, Shamsuddin, A. Kalam & Choudhury, M. Rahman, (2013), “Prospects and Challenges of the Animation Industry in Bangladesh”, International Journal of Computer Graphics & Animation (IJCGA) Vol.3, No.3, July 2013 [23]L. Wenxin, and H. Kekang, (2008) “Requirements of Multimedia Animation on Children's English Learning Education Technology and Training”, International Workshop on Geoscience and Remote Sensing. ETT and GRS, vol. 1, December 21- 22, Shanghai. [24] Heather L. Kirkorian, Ellen A. Wartella, & Daniel R. Anderson, (2008), Media and Young Children’s Learning, VOL. 18, NO. 1, pp. 39-61, www.futureofchildren.org
MULTIMEDIA MINING RESEARCH - AN OVERVIEW S.Vijayarani1 and A.Sakila2, 1Bharathiar University, India and 2M. Bharathiar University, India ABSTRACT Multimedia data mining is a popular research domain which helps to extract interesting knowledge from multimedia data sets such as audio, video, images, graphics, speech, text and combination of several types of data sets. Normally, multimedia data are categorized into unstructured and semi-structured data. These data are stored in multimedia databases and multimedia mining is used to find useful information from large multimedia database system by using various multimedia techniques and powerful tools. This paper provides the basic concepts of multimedia mining and its essential characteristics. Multimedia mining architectures for structured and unstructured data, research issues in multimedia mining, data mining models used for multimedia mining and applications are also discussed in this paper. It helps the researchers to get the knowledge about how to do their research in the field of multimedia mining. KEYWORDS Data Mining, Multimedia Mining, Architectures, Applications, Models FOR MORE DETAILS: http://airccse.org/journal/ijcga/papers/5115ijcga05.pdf VOLUME LINK: http://airccse.org/journal/ijcga/vol5.html
REFERENCES [1] Manjunath T.N, Ravindra S Hegadi, Ravikumar GK, “A Survey on Multimedia Data Mining and Its Relevance Today” IJCSNS International Journal of Computer Science and Network Security, VOL.10 No.11, November 2010. [2] Sarla More, Durgesh Kumar Mishra, “Multimedia Data Mining: A Survey” Pratibha: International Journal of science, spirituality, business and technology (ijssbt), vol. 1, no.1, march 2012 issn (print) 2277—7261. [3] Manjunath R, S. Balaji, “Review and Analysis of Multimedia Data Mining Tasks and Models”InternationalJournal of Innovative Research in Computer and Communication Engineering Vol.2, Special Issue 2, May 2014. [4] Bhavanithuraisingham, “Managing and mining multimedia Databases” International Journal on Artificial Intelligence Tools Vol. 13, No.3 (2004) 739-759. [5] JanuszSwierzowicz,“Multimedia Data Mining Trends and Challenges”. [6] Yu H, Wolf, Scenic classification methods for image and video databases. In In SPIE International Conference on Digital Image Storage and Archiving Systems, Vol. 2606,1995, pp. 363-371. [7] Mittal, Ankush, “An overview of multimedia content-based retrieval strategies”, Publication: Informatica, October 1 2006. [8] Valery A. Petrushin and Latifur Khan, “Multimedia Data Mining and Knowledge Discovery”, Springer, 2007 pp. 3- 17 [9] Jiawei Han, MichelineKamber “Data Mining: Concepts and Techniques” Published by Morgan Kaufmann, 2001. [10] Mori Y, Takahashi H, Oka R. Image-to-word transformation based on dividing and vector quantizing images with words. In: MISRM’99 First International Workshop on Multimedia Intelligent Storage and Retrieval management, 1999 [11] http://en.wikipedia.org/wiki?curid=14004969 [12] Chapter 25 Mining Multimedia Databases, Data Mining Techniques, Arun k pujari 1st Edition, Data warehousing, Data Mining and OLAP, Alex Berson ,smith.j. Stephen, [13] Data Mining Concepts and Techniques ,Jiawei Han and MichelineKamber, Data Mining Introductory and Advanced topics, Margaret H Dunham PEA, The Data Warehouse lifecycle toolkit , Ralph Kimball Wiley student Edition
[14] Ordenoz C, Omiecinski E. “Discovering association rules based on image content” In:ADL ’99: Proceedings of the the IEEE Forum on Research and Technology Advances in Digital libraries.Washington, DC: IEEE Computer Society; 1999, p.38. [15] V. Vijayakumar, R. Nedunchezhian “A study on video data mining”, International Journal of Multimedia Information Retrieval, October 2012, Volume 1, Issue 3, pp 153-172, Publisher Springer-Verlag. [16] http://www.comp.nus.edu.sg/~chidansh [17] Janusz Swierzowicz “Multimedia Data Mining Concept” . [18] Madiha Waris Farooque Azam Abdul Wahab Muzaffar A Survey of Issues in Multimedia Databases international Journal of Computer Applications (0975 – 8887) Volume 46 – No.7, May 2012 [19] S. Kotsiantis, D. Kanellopoulos, P. Pintelas, Multimedia Mining, (2004). ‘Multimedia mining’, WSEAS Transactions on Systems,. Vol. 3, No. 10, pp.3263–3268. Yu H, Wolf, Scenic classification methods for image and video databases. In In SPIE International Conference on Digital Image Storage and Archiving Systems, Vol. 2606,1995,pp. 363-371
PERFORMANCE ANALYSIS OF CHAIN CODE DESCRIPTOR FOR HAND SHAPE CLASSIFICATION Kshama Fating1 and Archana Ghotkar, Pune Institute of Computer Technology, India ABSTRACT Feature Extraction is an important task for any Image processing application. The visual properties of any image are its shape, texture and colour. Out of these shape description plays important role in any image classification. The shape description method classified into two types, contour base and region based. The contour base method concentrated on the shape boundary line and the region based method considers whole area. In this paper, contour based, the chain code description method was experimented for different hand shape. The chain code descriptor of various hand shapes was calculated and tested with different classifier such as k-nearest- neighbour (k-NN), Support vector machine (SVM) and Naive Bayes. Principal component analysis (PCA) was applied after the chain code description. The performance of SVM was found better than k-NN and Naive Bayes with recognition rate 93%. KEYWORDS Feature extraction, Chain code, k-NN, SVM, Naive Bayes FOR MORE DETAILS: http://airccse.org/journal/ijcga/papers/4214ijcga02.pdf VOLUME LINK: http://airccse.org/journal/ijcga/vol4.html
REFERENCES [1] S.Sridhar,(2012) “Digital Image Processing”, Oxford University Press. [2] R.S.Vaddi1, L. N.P.Boggavarapu1, H. D.Vankayalapati, K. R. Anne,(2011) “Contour detection using freeman chain code and approximation methods for real time object detection”, AJCSIT. [3] Jukka Iivarinen , Ari Visa,(1996) “Shape Recognition of Irregular Objects”, Proc. SPIE 2904. [4] Dr. Azzam Talal Sleit, Rahmeh Omar Jabay, (2006) “A Chain Code Approach for Recognizing Basic Shapes”, CSIT. [5] Pulipati Annapurna, Sriraman Kothuri, Srikanth Lukka, (2013) “Digit Recognition Using Freeman Chain Code”,JAIEM [6] Lili Ayu Wulandhari,Habibolah Haron,Ariffin Mohammad,(2008)“The Mapping Algorithm of Rrectangular Vertex Chain Code from Thinned Binary Image”, International Conference on Engineering Optimization. [7] Abdel-Badeeh M. Salem, Adel A. Sewisy, Usama A. Elyan,(2005) “A Vertex Chain Code Approach for Image Recognition”, ICGST-GVIP Journal, Volume 5, Issue3. [8] Yang Mingqiang, Kpalma Kidiyo, Ronsin Joseph,(2008) “ A survey of shape feature extraction techniques”, Pattern Recognition, Peng-Yeng Yin (Ed.)43-90. [9] Rafael C. Gonzalez,Richard E.Woods,(1998) “Digital Image Processing”, Addison Wesley. [10]Bribiesca E,(1999) “A New Chain Code. Pattern Recognition”, Vol. 32, issue 2, 235-25. [11]Manuele Bicego, Vittorio Murino,(2004) “Investigating Hidden Markov Models’ Capabilities in 2D Shape Classification”,IEEE Transaction on Pattern Analysis and Machine Intelligence,Vol.26, NO.2. [12]Serge Belongie, Jetendra Malik and Jan Puzicha,(2002) “Shape matching and Object recognition using Shape Context”, IEEE Transaction on Pattern Analysis and Machine Intelligence,Vol. 24. [13]Haibin Ling and David Jacobs, (2007) “Shape Classification Using the Inner- Distance”, IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 29, issue 2. [14]Thiago R. Trigo and Sergio Roberto M. Pellegrino,(2010) “An Analysis of Features for Hand GestureClassification”, IWSSIP - 17th International Conference on Systems, Signals and Image Processing. [15]V. C. Chen, (2004) “Evolution of Bayes, I CA, PCA and SVM Methods for classification”, RTOMPSET-080.
PROSPECTS AND CHALLENGES OF THE ANIMATION INDUSTRY IN BANGLADESH Md. Bharul Islam1, Abu Kalam Samshuddin1 and Moshiur Rahman Choudhury2, 1Daffodil International University, Bangladesh and 2Dreamer Donkey Private Limited, Bangladesh ABSTRACT Many developing countries are successfully developing their animation industries which are already contributed to their economic growth. It is noted that these countries have the potentials to become hubs for working international quality animation products due to low labor cost. For the purpose of reviewing the prospects of these industries, in Bangladesh, the researchers visited some selected animation studios in the capital city. Data was collected from 16 animation and multimedia studios using direct interviews, telephone conversations, and website visits etc. The main purpose of this study is to find out the prospects and challenges of animation industries in Bangladesh. KEYWORDS Feature extraction, Chain code, k-NN, SVM, Naive Bayes FOR MORE DETAILS: http://airccse.org/journal/ijcga/papers/3313ijcga02.pdf VOLUME LINK: http://airccse.org/journal/ijcga/vol3.html
REFERENCES [1] Islam, M Baharul (2013), “Motion analysis using distance and velocity-time function”, International Journal on Scientific Knowledge (Computing and Information technology), Vol. 2, No. 2, pp 1-6. [2] Edwin Michael, Afi Roshezry Abu Bakar, Ira Meilita Ibrahim, Geetha Veerappan, Norazleen Mohamad Noor, Lim Ean Heng, Taufik A. Latif, Ng Kar Yann, (2012) “A Comparative Study of Gender Roles in Animated Films”, Global Journal of Human Social Science, Vol. 12, No. 5, Version 1.0. [3] Hye-Kyung LEE (2010), “Animation industry at a crossroads”, Creative Industries Journal, Vol. 3, No. 3, pp 183-187. [4] Steve Roberts (2007), “Character Animation: 2D skills for better 3D”, second edition, Focal press (is an imprint of Elsevier), Jordan Hill, Oxford, UK. [5] Shegufta Yasmin (2011), “Contemporary Bangladeshi Commercial Cinema: A Perspective from Young Generation of Bangladesh”, ASA University Review, Vol. 5 No. 1, pp. 175-194. [6] National budget (2012), Ministry of 12_13/budget_speech/speech_en.pdf
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[13]Herwina Rosnan, Zarith Delaila, Abdul Aziz (2012) “Film Business in Malaysia: Challenges and Opportunities”, International Journal of Humanities and Social Science, Vol. 2 No. 12, pp. 198-202. [14]Ran Li, Kiyoshi Tomimatsu, Toru Kodama (2010) “Analysis of Major Problems Existing in Chinese Animation Industry” www.design.kyushu-u.ac.jp [15]Ted Tschang, Andrea Goldstein (2004), “Production and Political Economy in the Animation Industry: Why In-sourcing and Out-sourcing Occur”, Industrial Dynamics Innovation and Development (DRUID Summer Conference), Elsinore, Denmark, June 14-16. [16]Yamada Ken-ichi (2013) “Market competition in Animation industries between Japan and China: How to face China’s raising interest in promoting Domestically-Produced Animation” NHK Broadcasting Culture Research Institute (Media Research and Studies). [17]Michael D. Mattesi (2008) “Force Character Design from Life Drawing”, Focal press (is an imprint of Elsevier), Jordan Hill, Oxford, UK. [18]Richard Taylor (2013) “The Encyclopaedia of Animation Techniques”, Page One Publishing Private Limited, pp. 7.