Motion-based video segmentation with boundary refinement

Acoustics Speech and Signal Processing(2010)

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摘要
Motion-based video segmentation remains an important problem in video processing. A promising approach that has received significant attention formulates the problem as an energy minimization within a MAP-MRF framework. While a great deal of progress has been made toward finding robust and computationally reasonable motion segmentation methods, automatically generating such a segmentation that performs well at motion boundaries remains a challenging task. To address this problem, we propose and demonstrate a motion-based video segmentation method that uses an automatic color-based boundary refinement strategy to obtain a boundary-accurate segmentation within a reasonable computation time.
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关键词
Markov processes,image motion analysis,image segmentation,maximum likelihood estimation,video signal processing,MAP-MRF framework,Markov random field,automatic color-based boundary refinement,energy minimization,maximum a-posteriori framework,motion-based video segmentation,video signal processing,Color,Image segmentation,MAP Estimation,Motion Analysis,Video signal processing
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