DocumentCode :
3342441
Title :
High level feature: Head and body co-trakcing by Kalman filter
Author :
Chen, Chun-Hua ; Lin, Chung-Yuan ; Li, Sz-Yan ; Tsai, Tsung-Han
Author_Institution :
Dept. of Electr. Eng., Nat. Central Univ., Jhongli, Taiwan
fYear :
2010
fDate :
26-29 Sept. 2010
Firstpage :
725
Lastpage :
728
Abstract :
Tracking multiple targets in complex situation is challenging. The difficulties are tackled multiple targets with occlusions, especially when multiple involved targets are grouped and moving together in appearance. In this paper, we present a multiple targets tracking system for the management of occlusion problem. The proposed algorithm introduces a geometric shape co-tracking strategy. It decomposes targets into geometric shapes located on body and head parts based on reasonable target geometry consideration. Features selected from the decomposed geometric shapes then can be used to track targets through intersections such as occlusion. Projection histogram and ellipsoid shape model are adopted to manage decomposed geometric shapes corresponding to each target. Tracking is done through Kalman filtering process with high efficient and low complexity issue. Experimental results show that the occlusion of grouped targets can be tracked successfully on recent challenging benchmark sequences.
Keywords :
Kalman filters; feature extraction; image motion analysis; target tracking; Kalman filter; body cotracking; feature extraction; geometric shape cotracking strategy; head cotracking; target tracking; Ellipsoids; Feature extraction; Head; Histograms; Kalman filters; Shape; Target tracking; Kalman filter; correspondence; feature extraction; morphological; shape; tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2010 17th IEEE International Conference on
Conference_Location :
Hong Kong
ISSN :
1522-4880
Print_ISBN :
978-1-4244-7992-4
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2010.5651983
Filename :
5651983
Link To Document :
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