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Neural Network based Approach for Recognition Human Motion using Stationary Camera

by Rachana V. Modi, Tejas B. Mehta
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 25 - Number 6
Year of Publication: 2011
Authors: Rachana V. Modi, Tejas B. Mehta
10.5120/3032-4110

Rachana V. Modi, Tejas B. Mehta . Neural Network based Approach for Recognition Human Motion using Stationary Camera. International Journal of Computer Applications. 25, 6 ( July 2011), 43-47. DOI=10.5120/3032-4110

@article{ 10.5120/3032-4110,
author = { Rachana V. Modi, Tejas B. Mehta },
title = { Neural Network based Approach for Recognition Human Motion using Stationary Camera },
journal = { International Journal of Computer Applications },
issue_date = { July 2011 },
volume = { 25 },
number = { 6 },
month = { July },
year = { 2011 },
issn = { 0975-8887 },
pages = { 43-47 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume25/number6/3032-4110/ },
doi = { 10.5120/3032-4110 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:11:05.803136+05:30
%A Rachana V. Modi
%A Tejas B. Mehta
%T Neural Network based Approach for Recognition Human Motion using Stationary Camera
%J International Journal of Computer Applications
%@ 0975-8887
%V 25
%N 6
%P 43-47
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Video surveillance is currently one of the most active research topics in the computer vision community. During motion, the surveillance system can detect moving objects and identify them as humans, animals, vehicles. This strong interest is driven by a wide spectrum of promising applications in surveillance system such as Military security, Public and commercial security, etc. The model includes detection, feature extraction and recognition of people from image sequences involving humans. In proposed system frame differencing and Neural Network is used for moving object detection and recognition of human motion respectively. Experimental results show that human motion can be correctly classified.

References
  1. L. Wang, W. Hu, and T. Tan, 2003 “Recent developments in human motion analysis”, Pattern Recognition, Vol. 36,No. 3, pp.585-601
  2. C.M. Cyr and B.B. Kimia, “A Similarity-Based Aspect-Graph Approach to 3D Object Recognition,” Int’l J. Computer Vision, vol. 57, no. 1, 2004, pp. 5-22
  3. D. Toth and T. Aach, “Detection and Recognition of Moving Objects Using Statistical Motion Detection and Fourier Descriptors,” Proc. 12th Int’l Conf. Image Analysis and Processing (ICIAP 03), 2003, pp. 430-435.
  4. J.C. Russ, The Image Processing Handbook, 5th ed., CRC Press, Boca Raton, 2006, p. 589.
  5. J.B. Hayfron-Acquah, M.S. Nixon, and J.N. Carter, “Recognizing Human and Animal Movement by Symmetry,” Proc. IEEE Int. Conf. Image Processing (ICIP 01), 2001, pp. 290-293.
  6. J.C. Russ, The Image Processing Handbook, 5th ed., CRC Press, Boca Raton, 2006, p. 619
  7. Y. Bogomolov, G. Dror, S. Lapchev, E. Rivlin, and M. Rudzsky, “Classification of Moving Targets Based on Motion and Appearance,” Proc. British Machine Vision Conf. (BMVC 03), 2003, pp. 429-438.
  8. D.A. Forsyth and J. Ponce, Computer Vision: A Modern Approach, Prentice Hall, 2002, p. 615.
  9. James A. Anderson , Introduction to Neural Network , PHI, 1999
  10. Jain, R., and H. H. Nagel, "On the analysis of accumulative difference pictures from image sequences of real world scenes," IEEE Trans. PAMI, vol. PAMI-1, pp. 206-214, Apr. 1979.
  11. Rafael C. Gonzalez, Richard E. Woods, “Digital Image processing”, Second Edition. Prentice Hall, 2002
  12. Y. T. Zhou, V. Venkateswar, and R. Chellappa, “Edge detection and linear feature extraction using a 2-D random field model”, IEEE Trans. Pattern Analysis, Intell,11(1):84-95, Mach.1989
  13. Ripley BD. Pattern recognition and neural networks. Cambridge: Cambridge University Press; 1996.
Index Terms

Computer Science
Information Sciences

Keywords

Human Motion Recognition Neural Network

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