DocumentCode
3335764
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
Volume
3
fYear
2004
fDate
17-21 May 2004
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on
ISSN
1520-6149
Print_ISBN
0-7803-8484-9
Type
conf
DOI
10.1109/ICASSP.2004.1326466
Filename
1326466
Link To Document