We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 November 2024
Call for Paper
December Edition
IJCA solicits high quality original research papers for the upcoming December edition of the journal. The last date of research paper submission is 20 November 2024

Submit your paper
Know more
The week's pick
Responsive image
An Efficient Restoration Method for the Faint Dot Matrix Images

Ao Zhu Peng Cao
Random Articles
Reseach Article

A System for Dissecting the Video for Tracing Multiple Humans in Multifaceted Situation

by M. Hemalatha, V. Vinodhini, B. Sivaranjani
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 77 - Number 5
Year of Publication: 2013
Authors: M. Hemalatha, V. Vinodhini, B. Sivaranjani
10.5120/13390-1030

M. Hemalatha, V. Vinodhini, B. Sivaranjani . A System for Dissecting the Video for Tracing Multiple Humans in Multifaceted Situation. International Journal of Computer Applications. 77, 5 ( September 2013), 16-20. DOI=10.5120/13390-1030

@article{ 10.5120/13390-1030,
author = { M. Hemalatha, V. Vinodhini, B. Sivaranjani },
title = { A System for Dissecting the Video for Tracing Multiple Humans in Multifaceted Situation },
journal = { International Journal of Computer Applications },
issue_date = { September 2013 },
volume = { 77 },
number = { 5 },
month = { September },
year = { 2013 },
issn = { 0975-8887 },
pages = { 16-20 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume77/number5/13390-1030/ },
doi = { 10.5120/13390-1030 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:49:27.938822+05:30
%A M. Hemalatha
%A V. Vinodhini
%A B. Sivaranjani
%T A System for Dissecting the Video for Tracing Multiple Humans in Multifaceted Situation
%J International Journal of Computer Applications
%@ 0975-8887
%V 77
%N 5
%P 16-20
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Segmenting and tracking multiple humans is a challenging problem in complex situations in which extended occlusion, shadow and/or reflection exists. We tackle this problem with a 3D model-based approach. This method includes two stages, segmentation (detection) and tracking. Human hypotheses are generated by shape analysis of the foreground blobs using human shape model. The segmented human hypotheses are tracked with a Kalman filter with explicit handling of occlusion. Hypotheses are verified while they are tracked for the first second or so. The verification is done by walking recognition using an articulated human walking model. We propose a new method to recognize walking using motion template and temporal integration. Experiments show that our approach works robustly in very challenging Sequences.

References
  1. C. Bregler and J. Malik, Tracking people with Twists and Exponential Maps, CVPR'98.
  2. A. F. Bobick, J. W. Davis, The Recognition of Human Movement Using Temporal Templates, IEEE Trans. on PAMI, vol. 23, no. 3, 2001.
  3. R. Cutler and L. S. Davis, Robust Real-Time Periodic Motion Detection, Analysis, and Applications, IEEE Trans. on PAMI, vol. 22, no. 8, 2000.
  4. D. Forsyth and J. Ponce, Computer Vision: A Mordern Approach, Prentice-Hall, 2001.
  5. S. Hongeng and R. Nevatia, Multi-Agent Event Recognition, ICCV'01.
  6. I. Haritaoglu, D. Harwood and L. S. Davis, W4S: A Real- Time System for Detecting and Tracking People in 2 1/2 D, ECCV'98.
  7. S. Haritaoglu, D. Harwood and L. S. Davis, W4: Real-Time Surveillance of People and Their Activities, IEEE Trans. On PAMI, Vol. 22, No. 8, 2000.
  8. R. Rosales and S. Sclaroff, 3D Trajectory Recovery for Tracking Multiple Objects and Trajectory Guided Recognition of Actions, CVPR'99.
  9. W. Hu, T. Tan, L. Wang, and S. May bank, "A Survey on Visual Surveillance of Object Motion and Behaviors", IEEE Transactions on Systems, Mann, and Cybernetics, Part C: Applications and Reviews, vol. 34, No. 3, Aug. 2004, pp. 334-352.
  10. D. Comaniciu, V. Ramesh, P. Meer, "Real-time tracking of non-rigid objects using mean shift", Proc. IEEE Conference on Computer Vision and Pattern Recognition, Hilton Head Island, SC, 2000, pp. 142–149.
  11. C. Stauffer and W. E. L. Grimson, "Learning Patterns of Activity Using Real-Time Tracking," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 8, Aug. 2000.
  12. H. Tao, H. S. Sawhney, and R. Kumar, "A Sampling Algorithm for Tracking Multiple Objects," Proc. IEEE Workshop Vision Algorithms, 1999.
  13. H. Tao, H. S. Sawhney, and R. Kumar, "Object Tracking with Bayesian Estimation of Dynamic Layer Representations," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 1, Jan. 2002.
  14. A. M. Tekalp, Digital Video Processing. Prentice Hall, 1995.
  15. C. R. Wren, A. Azarbayejani, T. Darrell, and A. P. Pentland, "Pfinder: Real-Time Tracking of the Human Body," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 7, July 1997.
  16. T. Zhao, R. Nevatia, and F. Lv, "Segmentation and Tracking of Multiple Humans in Complex Situations," Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. 2, pp. 194-201, 2001.
  17. T. Zhao and R. Nevatia, "3D Tracking of Human Locomotion: A Tracking as Recognition Approach," Proc. Int'l Conf. Pattern Recognition, vol. 1, pp. 546-551, 2002.
  18. T. Zhao, "Model-Based Segmentation and Tracking of Multiple Humans in Complex Situations," PhD thesis, Univ. of Southern California, Los Angeles, 2003.
  19. A. Prati, R. Cucchiara, I. Mikic, and M. M. Trivedi, "Analysis and Detection of Shadows in Video Streams: A Comparative Evalua- tion," Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. 2, pp. 571-576, 2001.
  20. L. R. Rabiner, "A Tutorial on Hidden Markov Models and Slected Applications in Speech Recognition," Proc. IEEE, vol. 77, no. 2, 1989.
  21. K. Rohr, "Towards Model-Based Recognition of Human Move- ments in Image Sequences," CVGIP: Image Understanding, vol. 59, no. 1, pp. 94-115, 1994.
  22. R. Rosales and S. Sclaroff, "3D Trajectory Recovery for Tracking Multiple Objects and Trajectory Guided Recognition of Actions," Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. 2, pp. 117-123, 1999.
  23. H. Sidenbladh, M. J. Black, and D. J. Fleet, "Stochastic Tracking of 3D Human Figures Using 2D Image Motion," Proc. European Conf. Computer Vision, pp. 702-718, 2000.
  24. N. T. Siebel and S. Maybank, "Fusion of Multiple Tracking Algorithm for Robust People Tracking," Proc. European Conf. Computer Vision, pp. 373-387, 2002.
  25. Y. Song, X. Feng, and P. Perona, "Towards Detection of Human Motion," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 810-817, 2000.
  26. R. Kalman, "A New Approach to Linear Filtering and Prediction Problems," J. Basic Eng. , vol. 82, pp. 35-45, 1960.
  27. P. Kornprobst and G. Medioni, "Tracking Segmented Objects Using Tensor Voting," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 118-125, 2000.
  28. N. Krahnstover, M. Yeasin, and R. Sharma, "Towards a Unified Framework for Tracking and Analysis of Human Motion," Proc. IEEE Workshop Detection and Recognition of Events in Video, 2001.
  29. D. Liebowitz, A. Criminisi, and A. Zisserman, "Creating Archi- tectural Models from Images," Proc. EUROGRAPH Conf. , vol. 18, pp. 39-50, 1999.
  30. A. J. Lipton, H. Fujiyoshi, and R. S. Patil, "Moving Target Classification and Tracking from Real-Time Video," Proc. DARPA IU Workshop, pp. 129-136, 1998.
  31. F. Lv, T. Zhao, and R. Nevatia, "Self-Calibration of a Camera from a Walking Human," Proc. Int'l Conf. Pattern Recognition, vol. 1, pp. 562-567, 2002.
  32. S. J. McKenna, S. Jabri, Z. Duric, A. Rosenfeld, and H. Wechsler, "Tracking Groups of People," Computer Vision and Image Under- standing, vol. 80, no. 1, pp. 42-56, 2000.
Index Terms

Computer Science
Information Sciences

Keywords

Human Tracking Segmentation Kalman Filter Motion Template.

Powered by PhDFocusTM