This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Contour-Based Object Tracking with Occlusion Handling in Video Acquired Using Mobile Cameras
November 2004 (vol. 26 no. 11)
pp. 1531-1536
We propose a tracking method which tracks the complete object regions, adapts to changing visual features, and handles occlusions. Tracking is achieved by evolving the contour from frame to frame by minimizing some energy functional evaluated in the contour vicinity defined by a band. Our approach has two major components related to the visual features and the object shape. Visual features (color, texture) are modeled by semiparametric models and are fused using independent opinion polling. Shape priors consist of shape level sets and are used to recover the missing object regions during occlusion. We demonstrate the performance of our method on real sequences with and without object occlusions.

[1] C. 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, pp. 780-785, July 1997.
[2] 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, pp. 747-757, Aug. 2000.
[3] D. Comaniciu, V. Ramesh, and P. Meer, Kernel-Based Object Tracking IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 5, pp. 564-575, May 2003.
[4] A.D. Jepson, D.J. Fleet, and T.F. El-Maraghi, Robust Online Appearance Models for Visual Tracking IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 10, Oct. 2003.
[5] M. Kass, A. Witkin, and D. Terzopoulos, Snakes: Active Contour Models Int'l J. Computer Vision, vol. 1, 1988.
[6] V. Caselles, R. Kimmel, and G. Sapiro, "Geodesic Active Contours," Proc. IEEE ICCV-95, pp. 694-699, 1995.
[7] N. Paragios and R. Deriche, Geodesic Active Contours and Level Sets for the Detection and Tracking of Moving Objects IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, pp. 1-15, 2000.
[8] M. Bertalmio, G. Sapiro, and G. Randall, Morphing Active Contours IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 7, July 2000.
[9] S.C. Zhu and A. Yuille, “Region Competition: Unifying Snakes, Region Growing and Bayes/MDL for Multiband Image Segmentation,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 18, pp. 884-900, 1996.
[10] S. Jehan-Besson and M. Barlaud, Video Object Segmentation Using Eulerian Region-Based Active Contours Proc. IEEE Int'l Conf. Computer Vision, 2001.
[11] N. Paragios and R. Deriche, Geodesic Active Regions and Level Set Methods for Supervised Texture Segmentation Int'l J. Computer Vision, vol. 46, no. 3, pp. 223-247, 2002.
[12] A. Yezzi, L. Zollei, and T. Kapur, A Variational Framework for Joint Segmentation and Registration Proc. Workshop Math. Methods in Biomedical Image Analysis, 2001.
[13] J. Rittscher and A. Blake, A Probabilistic Background Model for Tracking Proc. Europen Conf. Computer Vision, vol. 2, 2000.
[14] A. Mansouri, Region Tracking via Level Set PDEs Without Motion Computation IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 7, pp. 947-961, July 2002.
[15] D. Cremers, T. Kohlberger, and C. Schnörr, Nonlinear Shape Statistics in Mumford-Shah Based Segmentation Proc. Europen Conf. Computer Vision, 2002.
[16] W.T. Freeman and E.H. Adelson, "The Design and Use of Steerable Filters," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 13, pp. 891-906, 1991.
[17] J. Sethian, Level Set Methods: Evolving Interfaces in Geometry, Fluid Mechanics Computer Vision and Material Sciences. Cambridge Univ. Press, 1999.

Index Terms:
Contour tracking, shape priors, occlusion handling, level sets.
Citation:
Alper Yilmaz, Xin Li, Mubarak Shah, "Contour-Based Object Tracking with Occlusion Handling in Video Acquired Using Mobile Cameras," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 11, pp. 1531-1536, Nov. 2004, doi:10.1109/TPAMI.2004.96
Usage of this product signifies your acceptance of the Terms of Use.