The week's pick
Random Articles
Reseach Article
Human Action Recognition using Image Processing and Artificial Neural Networks
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 80 - Number 9 |
| Year of Publication: 2013 |
| Authors: Chaitra B. H, Anupama H. S, N. K Cauvery |
10.5120/13891-1826
|
Chaitra B. H, Anupama H. S, N. K Cauvery . Human Action Recognition using Image Processing and Artificial Neural Networks. International Journal of Computer Applications. 80, 9 ( October 2013), 31-34. DOI=10.5120/13891-1826
Abstract
Human action recognition is an important technique and has drawn the attention of many researchers due to its varying applications such as security systems, medical systems, entertainment. Action recognition is an interesting and a challenging topic of computer vision research due to its prospective use in proactive computing. The developed algorithm for the human action recognition system, which uses the two-dimensional discrete cosine transform(2D-DCT) for image compression and the self organizing map(SOM) neural network for recognition purpose, is simulated in MATLAB. By using 2D-DCT we extract image vectors and these vectors become the input to neural network classifier, which uses self organizing map algorithm to recognize elementary actions from the images (trained). In this paper we have developed and illustrated a recognition system for human actions using a novel self organizing map based retrieval system. SOM has good feature extracting property due to its topological ordering. Using an image database of 30 action images, containing six subjects and each subject having five images with different body postures reflects that the action recognition rate using one of the neural network algorithm SOM is 98. 16%.
References
- L. Weilun, H. Jungong, and P. With, "Flexible human behavior analysis framework for video surveillance applications," Int. J. Digital Multimedia Broadcast. , vol. 2010, pp. 920121-1–920121-9, Jan. 2010.
- G. Strang, "The discrete cosine transform", SIAM Review, vol. 41, No. 1, pp. 135 - 147, 1999.
- W. B. Pennebaker and J. L. Mitchell, "JPEG – Still Image Data Compression Standard," Newyork: International Thomsan Publishing, 1993.
- R. C. Gonzalez and R. E. Woods, "Digital Image Processing," 3rd Edition, Prentice Hall, 2008, ISBN-13: 9780131687288.
- P. Barr, J. Noble, and R. Biddle, "Video game values: Human-computer interaction and games," Interact. Comput. , vol. 19, no. 2, pp. 180–195, Mar. 2007.
- T. Kohonen, "Self-Organizing Maps," Springer, Berlin, Heidelberg, 1995.
- Teuvo Kohonen "Self-Organizing Map," Proceedings of the IEEE, vol. 78, No. 9, September 1990.
- Alexandros Iosifidis, Anastasios Tefas, "View-Invariant Action Recognition Based on Artificial Neural Networks," IEEE transactions on neural networks and learning systems, vol. 23, no. 3, March 2012.
- Weilong Yang, Yang Wang, and Greg Mori "Recognizing human actions from still Images with Latent Pose," School of Computing Science, Simon Fraser University, Burnaby, BC, Canada, September 2012.
- Keerti Keshav Kanchi, "Facial Expression Recognition using Image Processing and Neural Network", International Journal of Computer Science & Engineering Technology (IJCSET), ISSN: 2229-3345, Vol. 4 No. 05 May 2013.
Index Terms
Keywords