Evaluating multi-scale over-segment and its contribution to real scene stereo matching by high-order MRFs

Yiran Xie*, Rui Cao, Hanyang Tong, Sheng Liu, Nianjun Liu

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    The paper is to propose a framework to qualitatively and quantitatively evaluate five of state-of-the-art over-segment approaches. Moreover upon over-segments evaluation, an efficient approach is developed for dense stereo matching through robust higher-order MRFs and graph cut based optimization, which combines the conventional data and smoothness terms with the robust higher-order potential term. The experimental results on real-scene data sets clearly demonstrate that our over-segment-based higher-order stereo matching approach outperforms conventional stereo matching algorithms, as well as how over-segments improve the stereo matching process.

    Original languageEnglish
    Title of host publicationProceedings - 2010 Digital Image Computing
    Subtitle of host publicationTechniques and Applications, DICTA 2010
    Pages235-240
    Number of pages6
    DOIs
    Publication statusPublished - 2010
    EventInternational Conference on Digital Image Computing: Techniques and Applications, DICTA 2010 - Sydney, NSW, Australia
    Duration: 1 Dec 20103 Dec 2010

    Publication series

    NameProceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010

    Conference

    ConferenceInternational Conference on Digital Image Computing: Techniques and Applications, DICTA 2010
    Country/TerritoryAustralia
    CitySydney, NSW
    Period1/12/103/12/10

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