Multiple random walkers and their application to image cosegmentation

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    81 Citations (Scopus)

    Abstract

    A graph-based system to simulate the movements and interactions of multiple random walkers (MRW) is proposed in this work. In the MRW system, multiple agents traverse a single graph simultaneously. To achieve desired interactions among those agents, a restart rule can be designed, which determines the restart distribution of each agent according to the probability distributions of all agents. In particular, we develop the repulsive rule for data clustering. We illustrate that the MRW clustering can segment real images reliably. Furthermore, we propose a novel image cosegmentation algorithm based on the MRW clustering. Specifically, the proposed algorithm consists of two steps: inter-image concurrence computation and intra-image MRW clustering. Experimental results demonstrate that the proposed algorithm provides promising cosegmentation performance.

    Original languageEnglish
    Title of host publicationIEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015
    PublisherIEEE Computer Society
    Pages3837-3845
    Number of pages9
    ISBN (Electronic)9781467369640
    DOIs
    Publication statusPublished - 2015 Oct 14
    EventIEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015 - Boston, United States
    Duration: 2015 Jun 72015 Jun 12

    Publication series

    NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
    Volume07-12-June-2015
    ISSN (Print)1063-6919

    Other

    OtherIEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015
    Country/TerritoryUnited States
    CityBoston
    Period15/6/715/6/12

    Bibliographical note

    Publisher Copyright:
    © 2015 IEEE.

    ASJC Scopus subject areas

    • Software
    • Computer Vision and Pattern Recognition

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