Stereo image segmentation

Details Stereo image segmentation Stereo image segmentation

2011-08-02

2011-08-02

Ahmed, Samir A (Department: 2624)

Image analysis

Image segmentation

C382S154000, C382S175000, C382S275000, C382S277000, C382S180000, C348S340000, C348S157000, C348S159000, C348S014160, C345S619000

Reexamination Certificate

active

07991228

ABSTRACT:
Real-time segmentation of foreground from background layers in binocular video sequences may be provided by a segmentation process which may be based on one or more factors including likelihoods for stereo-matching, color, and optionally contrast, which may be fused to infer foreground and/or background layers accurately and efficiently. In one example, the stereo image may be segmented into foreground, background, and/or occluded regions using stereo disparities. The stereo-match likelihood may be fused with a contrast sensitive color model that is initialized or learned from training data. Segmentation may then be solved by an optimization algorithm such as dynamic programming or graph cut. In a second example, the stereo-match likelihood may be marginalized over foreground and background hypotheses, and fused with a contrast-sensitive color model that is initialized or learned from training data. Segmentation may then be solved by an optimization algorithm such as a binary graph cut.

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