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Vision Based Gesture Recognition Using Neural Networks Approaches: A Review
Noor Adnan Ibraheem, Rafiqul Z. Khan
Pages - 1 - 14     |    Revised - 15-01-2012     |    Published - 21-02-2012
Volume - 3   Issue - 1    |    Publication Date - February 2012  Table of Contents
Neural Networks, Human Computer Interaction, Gesture Recognition System, Gesture Features, Static Gestures, Dynamic Gestures
The aim of gesture recognition researches is to create system that easily identifies gestures, and use them for device control, or convey in formations. In this paper we are discussing researches done in the area of hand gesture recognition based on Artificial Neural Networks approaches. Several hand gesture recognition researches that use Neural Networks are discussed in this paper, comparisons between these methods were presented, advantages and drawbacks of the discussed methods also included, and implementation tools for each method were presented as well.
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1 G. R. S. Murthy & R. S. Jadon. (2009, Dec). “A Review Of Vision Based Hand Gestures Recognition,” International Journal of Information Technology and Knowledge Management, vol. 2(2), pp. 405-410.
2 P. Garg, N. Aggarwal and S. Sofat. (2009). “Vision Based Hand Gesture Recognition,” World Academy of Science, Engineering and Technology vol. 49, pp. 972-977.
3 Gesture Wikipedia website. http://en.wikipedia.org/wiki/Gesture
4 Marcus Vinicius Lamar, “Hand Gesture Recognition using T-CombNET A Neural Network Model dedicated to Temporal Information Processing,” Doctoral Thesis, Institute of Technology, Japan, 2001.
5 S. Mitra, and T. Acharya. (2007, May). “Gesture Recognition: A Survey” IEEE Transactions on systems, Man and Cybernetics, Part C: Applications and reviews, vol. 37 (3), pp. 311-324, available: doi: 10.1109/TSMCC.2007.893280.
6 Thomas B. Moeslund and Erik Granum. (2001, Mar.). “A Survey of Computer Vision-Based Human Motion Capture,” Elseiver Computer Vision and Image Understanding vol. 81(3),pp. 231–268. Available: doi: 10.1006/cviu.2000.0897
7 Joseph J. LaViola Jr., “A Survey of Hand Posture and Gesture Recognition Techniques and Technology,” Master Thesis, NSF Science and Technology Center for Computer Graphics and Scientific Visualization, USA, 1999.
8 SANJAY MEENA, “A Study on Hand Gesture Recognition Technique,” Master thesis,Department of Electronics and Communication Engineering, National Institute of Technology, India, 2011.
9 M. M. Hasan, P. K. Mishra. (2010, Dec.). “HSV Brightness Factor Matching for Gesture Recognition System”, International Journal of Image Processing (IJIP), vol. 4(5), pp. 456-467.
10 Laura Dipietro, Angelo M. Sabatini, and Paolo Dario.(2008, Jul). “Survey of Glove-Based Systems and their applications,” IEEE Transactions on systems, Man and Cybernetics, Part C: Applications and reviews, Vol. 38, No. 4, pp. 461-482. Available: doi:10.1109/TSMCC.2008.923862
11 EngineersGarage. Artificial Neural Networks (ANN): Introduction, Details & Applications.Available: http://www.engineersgarage.com/articles/artificial-neural-networks
12 S. Haykin. (1999) “Neural Networks - A Comprehensive Foundation”, Englewood Cliffs, NJ:Prentice-Hall, Second Edition. Available: http://www.amazon.de/Neural-NetworksComprehensive-Simon-Haykin/dp/0132733501
13 Shweta K. Yewale, Pankaj K. Bharne. (2011, Apr.) “Artificial Neural Network Approach For Hand Gesture Recognition”, International Journal of Engineering Science and Technolog(IJEST), vol. 3(4), pp. 2603- 2608.
14 Ben Krose, and Patrick van der Smagtan (1996). “An introduction to Neural Networks,” the University of Amsterdam, eighth edition.
15 Neuro AI - Intelligent systems and Neural Networks: Neural networks: A requirement for intelligent systems. http://www.learnartificialneuralnetworks.com/
16 Types of artificial neural networks, Recurrent neural network, Neural network. From Wikipedia Website.
17 L.R. Medsker, and L.C. Jain, ”Recurrent Neural Networks Design and Applications,” CRC Press, 2001.
18 Kouichi Murakami and Hitomi Taguchi. (1999). “Gesture Recognition using Recurrent Neural Networks, ” ACM Proceedings of the SIGCHI conference on Human factors in computing systems: Reaching through technology (CHI '91), pp. 237-242. Available: doi:10.1145/108844.108900
19 Self-organizing map. From Wikipedia Website.
20 Shyam M. Guthikonda, “Kohonen Self-Organizing Maps,” Wittenberg University, December 2005.
21 Ankit Chaudhary, J. L. Raheja, Karen Das, and Sonia Raheja. (2011, Feb). “Intelligent Approaches to interact with Machines using Hand Gesture Recognition in Natural way A Survey,” International Journal of Computer Science & Engineering Survey (IJCSES), vol.2(1).
22 Jian-kang Wu. (1994). “Neural networks and Simulation methods,” Marcel Dekker, Inc.,USA. Available:http://books.google.co.in/books/about/Neural_networks_and_simulation_methods.html?id=95iQOxLDdK4C&redir_esc=y.
23 Mahmoud Elmezain, Ayoub Al-Hamadi, Jorg Appenrodt, and Bernd Michaelis. (2009). “A Hidden Markov Model-Based Isolated and Meaningful Hand Gesture Recognition,”International Journal of Electrical and Electronics Engineering, pp. 156-163.
24 Ruiduo Yang and Sudeep Sarkar. (2006, Jul.). “Gesture Recognition using Hidden Markov Models from Fragmented Observations,” IEEE Proceedings of the Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’06). pp. 766 – 773,Available: doi: 10.1109/CVPR.2006.126
25 Verma R., Dev A. (2009, Dec.). ” Vision based hand gesture recognition using finite state machines and fuzzy logic”, IEEE International Conference on Ultra Modern Telecommunications & Workshops, (ICUMT '09), pp. 1-6, Petersburg, doi:10.1109/ICUMT.2009.5345425
26 Tin Hninn H. Maung. (2009). “Real-Time Hand Tracking and Gesture Recognition System Using Neural Networks,” World Academy of Science, Engineering and Technology 50, pp.466- 470.
27 Manar Maraqa, Raed Abu-Zaiter. (2008, Aug.). “Recognition of Arabic Sign Language (ArSL) Using Recurrent Neural Networks,” IEEE First International Conference on the Applications of Digital Information and Web Technologies, (ICADIWT 2008), pp. 478-48.Available: doi: 10.1109/ICADIWT.2008.4664396
28 Gonzalo Bailador, Daniel Roggen, and Gerhard Tröster. (2007). “Real time gesture recognition using Continuous Time Recurrent Neural Networks”, Proceedings of the ICST 2nd international conference on Body area networks.
29 E. Stergiopoulou, N. Papamarkos. (2009, Dec.). “Hand gesture recognition using a neural network shape fitting technique,” Elsevier Engineering Applications of Artificial Intelligence,vol. 22(8) ,pp. 1141–1158.available: doi: 10.1016/j.engappai.2009.03.008
30 Xingyan Li. (2003). “Gesture Recognition Based on Fuzzy C-Means Clustering Algorithm”,Department of Computer Science. The University of Tennessee Knoxville.
31 Cheng-Chang Lien, Chung-Lin Huang. (1999). “The model-based dynamic hand posture identification using genetic algorithm”, Springer Machine Vision and Applications, vol. 11(3),pp. 107–121. Available: doi: 10.1007/s001380050095
32 Ying Wu, Thomas S. Huang. (1999) “Vision-Based Gesture Recognition: A Review,”Beckman Institute 405 N. Mathews, University of Illinois at Urbana-Champaign, Urbana.
Mr. Noor Adnan Ibraheem
AMu university - India
Mr. Rafiqul Z. Khan
AMu university - India