Fixed point probability field for complex occlusion handling

In this paper, we show that in a multi-camera context, we can effectively handle occlusions in real-time at each frame independently, even when the only available data comes from the binary output of a simple blob detector, and the number of present individuals is a priori unknown. We start from occupancy probability estimates in a top view and rely on a generative model to yield probability images to be compared with the actual input images. We then refine the estimates so that the probability images match the binary input images as well as possible. We demonstrate the quality of our results on several sequences involving complex occlusions.

[1]  L. Davis,et al.  M2Tracker: A Multi-View Approach to Segmenting and Tracking People in a Cluttered Scene , 2003, International Journal of Computer Vision.

[2]  Larry S. Davis,et al.  W4S: A real-time system detecting and tracking people in 2 1/2D , 1998, ECCV.

[3]  Ivana Mikic,et al.  Video Processing and Integration from Multiple Cameras , 1998 .

[4]  Rainer Stiefelhagen,et al.  Towards vision-based 3-D people tracking in a smart room , 2002, Proceedings. Fourth IEEE International Conference on Multimodal Interfaces.

[5]  James Black,et al.  Multi view image surveillance and tracking , 2002, Workshop on Motion and Video Computing, 2002. Proceedings..

[6]  Ramakant Nevatia,et al.  Tracking multiple humans in crowded environment , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[7]  James J. Little,et al.  A Boosted Particle Filter: Multitarget Detection and Tracking , 2004, ECCV.

[8]  Larry S. Davis,et al.  W/sup 4/: Who? When? Where? What? A real time system for detecting and tracking people , 1998, Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition.

[9]  Kiriakos N. Kutulakos,et al.  A Probabilistic Theory of Occupancy and Emptiness , 2002, ECCV.

[10]  J. Krumm,et al.  Multi-camera multi-person tracking for EasyLiving , 2000, Proceedings Third IEEE International Workshop on Visual Surveillance.

[11]  R. Cipolla,et al.  A probabilistic framework for space carving , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[12]  Jake K. Aggarwal,et al.  Automatic tracking of human motion in indoor scenes across multiple synchronized video streams , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[13]  K. Otsuka,et al.  Multiview occlusion analysis for tracking densely populated objects based on 2-D visual angles , 2004, CVPR 2004.

[14]  Pascal Fua,et al.  Fixed Point Probability Field for Occlusion Handling , 2004 .

[15]  Mubarak Shah.  Tracking people in presence of occlusion , 2000 .

[16]  Mubarak Shah,et al.  Tracking in uncalibrated cameras with overlapping field of view , 2001 .

[17]  Dariu Gavrila,et al.  A Bayesian Framework for Multi-cue 3D Object Tracking , 2004, ECCV.

[18]  Isaac Cohen,et al.  Jeju Island , Korea TRACKING PEOPLE IN CROWDED SCENES ACROSS MULTIPLE CAMERAS , 2004 .