Adaptive Graph-Cut Algorithm to Video Moving Objects Segmentation

An adaptive Graph-cut algorithm to video moving objects segmentation was proposed. By the Kalman prediction of the number of objectives pixels and objectives-background pixel-pairs, and adaptive updating of the nodes flux, the Graph-cut algorithm was successfully applied to video moving objects segm...

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Bibliographic Details
Published in2009 2nd International Congress on Image and Signal Processing pp. 1 - 5
Main Authors Guo Chun-sheng, Wang Pan
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2009
Subjects
Application software
Cameras
Computer vision
Educational institutions
Image segmentation
Kalman filters
Markov random fields
Object segmentation
Testing
Virtual colonoscopy
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ISBN1424441293
9781424441297
DOI10.1109/CISP.2009.5303436

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Summary:An adaptive Graph-cut algorithm to video moving objects segmentation was proposed. By the Kalman prediction of the number of objectives pixels and objectives-background pixel-pairs, and adaptive updating of the nodes flux, the Graph-cut algorithm was successfully applied to video moving objects segmentation. It was achieve to continuous global optimization segmentation of video moving objects. Experimental results show that the quantitative detection parameters of this algorithm are performing well in complex background conditions.
ISBN:1424441293
9781424441297
DOI:10.1109/CISP.2009.5303436