Motion layer extraction in the presence of occlusion using graph cuts

    Authors

    J. J. Xiao;M. Shah

    Comments

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    Abbreviated Journal Title

    IEEE Trans. Pattern Anal. Mach. Intell.

    Keywords

    layer-based motion segmentation; video analysis; graph cuts; level set; representation; occlusion order constraint; SEGMENTATION; TRACKING; Computer Science, Artificial Intelligence; Engineering, Electrical &; Electronic

    Abstract

    Extracting layers from video is very important for video representation, analysis, compression, and synthesis. Assuming that a scene can be approximately described by multiple planar regions, this paper describes a robust and novel approach to automatically extract a set of affine or projective transformations induced by these regions, detect the occlusion pixels over multiple consecutive frames, and segment the scene into several motion layers. First, after determining a number of seed regions using correspondences in two frames, we expand the seed regions and reject the outliers employing the graph cuts method integrated with level set representation. Next, these initial regions are merged into several initial layers according to the motion similarity. Third, an occlusion order constraint on multiple frames is explored, which enforces that the occlusion area increases with the temporal order in a short period and effectively maintains segmentation consistency over multiple consecutive frames. Then, the correct layer segmentation is obtained by using a graph cuts algorithm and the occlusions between the overlapping layers are explicitly determined. Several experimental results are demonstrated to show that our approach is effective and robust.

    Journal Title

    Ieee Transactions on Pattern Analysis and Machine Intelligence

    Volume

    27

    Issue/Number

    10

    Publication Date

    1-1-2005

    Document Type

    Article

    Language

    English

    First Page

    1644

    Last Page

    1659

    WOS Identifier

    WOS:000231086700011

    ISSN

    0162-8828

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