Title :
Robust two-camera tracking using homography
Author :
Yue, Zhanfeng ; Zhou, Shaohua Kevin ; Chellappa, Rama
Author_Institution :
Dept. of Electr. & Comput. Eng., Maryland Univ., College Park, MD, USA
Abstract :
The paper introduces a two view tracking method which uses the homography relation between the two views to handle occlusions. An adaptive appearance-based model is incorporated in a particle filter to realize robust visual tracking. Occlusion is detected using robust statistics. When there is occlusion in one view, the homography from this view to other views is estimated from previous tracking results and used to infer the correct transformation for the occluded view. Experimental results show the robustness of the two view tracker.
Keywords :
Monte Carlo methods; image sequences; nonlinear filters; optical tracking; video signal processing; homography; nonlinear filter; occlusions; particle filter; robust statistics; sequential Monte Carlo framework; two view tracking method; two-camera tracking; video frame processing; visual tracking; Bayesian methods; Cameras; Collaboration; Fuses; Government; Maximum likelihood detection; Motion estimation; Robustness; Statistics; Target tracking;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on
Print_ISBN :
0-7803-8484-9
DOI :
10.1109/ICASSP.2004.1326466