DocumentCode :
2542172
Title :
Bidirectional tracking using trajectory segment analysis
Author :
Sun, Jian ; Zhang, Weiwei ; Tang, Xiaoou ; Shum, Heung-Yeung
Author_Institution :
Microsoft Res. Asia, Beijing, China
Volume :
1
fYear :
2005
fDate :
17-21 Oct. 2005
Firstpage :
717
Abstract :
In this paper, we present a novel approach to keyframe-based tracking, called bi-directional tracking. Given two object templates in the beginning and ending keyframes, the bi-directional tracker outputs the MAP (maximum a posterior) solution of the whole state sequence of the target object in the Bayesian framework. First, a number of 3D trajectory segments of the object are extracted from the input video, using a novel trajectory segment analysis. Second, these disconnected trajectory segments due to occlusion are linked by a number of inferred occlusion segments. Last, the MAP solution is obtained by trajectory optimization in a coarse-to-fine manner. Experimental results show the robustness of our approach with respect to sudden motion, ambiguity, and short and long periods of occlusion.
Keywords :
Bayes methods; image motion analysis; image segmentation; image sequences; maximum likelihood estimation; video signal processing; 3D trajectory segment extraction; Bayesian framework; bidirectional tracking; image sequence; keyframe-based tracking; maximum a posterior solution; object templates; occlusion; target object; trajectory segment analysis; Bayesian methods; Bidirectional control; Hidden Markov models; Recursive estimation; Sun; Target tracking; Trajectory; Video compression; Video sequences; Video surveillance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on
ISSN :
1550-5499
Print_ISBN :
0-7695-2334-X
Type :
conf
DOI :
10.1109/ICCV.2005.49
Filename :
1541324
Link To Document :
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