A. O. Ercan, A. El Gamal and L. J. Guibas, Object Tracking in the Presence of Occlusions via a Camera Network, in Proceedings of 6th Int'l Conference on Information Processing in Sensor Networks (IPSN), pp. 509-518, Cambridge, MA, April 2007.

Abstract:

This paper describes a sensor network approach to tracking a single object in the presence of static and moving occluders using a network of cameras. To conserve communication bandwidth and energy, each camera rst performs simple local processing to reduce each frame to a scan line. This information is then sent to a cluster head to track a point object. We assume the locations of the static occluders to be known, but only prior statistics on the positions of the moving occluders are available. A noisy perspective camera measurement model is presented, where occlusions are captured through an occlusion indicator function. An auxiliary particle lter that incorporates the occluder information is used to track the object. Using simulations, we investigate (i) the dependency of the tracker performance on the accuracy of the moving occluder priors, (ii) the tradeoff between the number of cameras and the occluder prior accuracy required to achieve a prescribed tracker performance, and (iii) the importance of having occluder priors to the tracker performance as the number of occluders increases. We generally nd that computing moving occluder priors may not be worthwhile, unless it can be obtained cheaply and to a reasonable accuracy. Preliminary experimental results are provided.

Bibtex: 

@inproceedings{eeg-otpocn-ipsn07,
 author = {Ali Ozer Ercan and Abbas El Gamal and Leonidas J. Guibas},
 title = {Object tracking in the presence of occlusions via a camera network},
 booktitle = {IPSN '07: Proceedings of the 6th international conference on Information processing in sensor networks},
 year = {2007},
 pages = {509--518},
 location = {Cambridge, Massachusetts, USA},
 publisher = {ACM Press},
 address = {New York, NY, USA},
 }