DocumentCode :
2466450
Title :
Region-based optical flow estimation
Author :
Fuh, Chiou-Shann ; Maragos, Petros
Author_Institution :
Div. of Appl. Sci., Harvard Univ., Cambridge, MA, USA
fYear :
1989
fDate :
4-8 Jun 1989
Firstpage :
130
Lastpage :
135
Abstract :
A correspondence method is developed for determining optical flow where the primitive motion tokens to be matched between consecutive time frames are regions. The computation of optical flow consists of three stages: region extraction, region matching, and optical flow smoothing. The computation is completed by smoothing the initial optical flow, where the sparse velocity data are either smoothed with a vector median filter or interpolated to obtain dense velocity estimates by using a motion-coherence regularization. The proposed region-based method for optical flow is simple, computationally efficient, and more robust than iterative gradient methods, especially for medium-range motion
Keywords :
optical information processing; pattern recognition; picture processing; correspondence method; dense velocity estimates; motion-coherence regularization; optical flow estimation; pattern recognition; picture processing; primitive motion tokens; region extraction; region matching; smoothing; sparse velocity data; vector median filter; Data flow computing; Data mining; Gradient methods; Image motion analysis; Iterative methods; Motion estimation; Optical computing; Optical filters; Robustness; Smoothing methods;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 1989. Proceedings CVPR '89., IEEE Computer Society Conference on
Conference_Location :
San Diego, CA
ISSN :
1063-6919
Print_ISBN :
0-8186-1952-x
Type :
conf
DOI :
10.1109/CVPR.1989.37840
Filename :
37840
Link To Document :
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