DocumentCode :
2635241
Title :
Object tracking based on optical flow and depth
Author :
Okada, Ryuzo ; Shirai, Yoshiaki ; Miura, Jun
Author_Institution :
Dept. of Mech. Eng. for Comput.-Controlled Machinery, Osaka Univ., Japan
fYear :
1996
fDate :
8-11 Dec 1996
Firstpage :
565
Lastpage :
571
Abstract :
This paper describes a method to track an object based on optical flow and depth. The velocity and the depth of the target object are estimated from the histograms of the velocity and that of the disparity. A target region is extracted by Baysian inference using optical flow, disparity and the predicted target location. This method works even if tracking with either velocity data or disparity data alone may fail. Occlusion of the target can also be detected from the abrupt change of the disparity of the target region. Our method successfully tracked a moving person using a real image sequence
Keywords :
Bayes methods; filtering theory; image sequences; probability; stereo image processing; target tracking; tracking; Baysian inference; depth; disparity; histograms; moving person; object tracking; occlusion; optical flow; Data mining; Equations; Filtering; Gradient methods; Image motion analysis; Machinery; Mechanical engineering; Optical filters; Optical recording; Target tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multisensor Fusion and Integration for Intelligent Systems, 1996. IEEE/SICE/RSJ International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-3700-X
Type :
conf
DOI :
10.1109/MFI.1996.572231
Filename :
572231
Link To Document :
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