Probabilistic visibility for multi-view stereo

Carlos Hernández*, George Vogiatzis, Roberto Cipolla

*Corresponding author for this work

    Research output: Chapter in Book/Published conference outputConference publication

    Abstract

    We present a new formulation to multi-view stereo that treats the problem as probabilistic 3D segmentation. Previous work has used the stereo photo-consistency criterion as a detector of the boundary between the 3D scene and the surrounding empty space. Here we show how the same criterion can also provide a foreground/background model that can predict if a 3D location is inside or outside the scene. This model replaces the commonly used naive foreground model based on ballooning which is known to perform poorly in concavities. We demonstrate how the probabilistic visibility is linked to previous work on depth-map fusion and we present a multi-resolution graph-cut implementation using the new ballooning term that is very efficient both in terms of computation time and memory requirements.

    Original languageEnglish
    Title of host publication2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07
    PublisherIEEE
    ISBN (Print)1424411807, 9781424411801
    DOIs
    Publication statusPublished - 16 Jul 2007
    Event2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07 - Minneapolis, MN, United States
    Duration: 17 Jun 200722 Jun 2007

    Publication series

    NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
    ISSN (Print)1063-6919

    Conference

    Conference2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07
    Country/TerritoryUnited States
    CityMinneapolis, MN
    Period17/06/0722/06/07

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