A novel object-oriented stereo matching on multi-scale superpixels for low-resolution depth mapping

Hanyang Tong*, Sheng Liu, Nianjun Liu, Nick Barnes

*Corresponding author for this work

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

    4 Citations (Scopus)

    Abstract

    This paper presents a novel object-oriented stereo matching on multi-scale superpixels to generate a low-resolution depth map. It overcomes the classic downsampling methods' disadvantages, such as boundary blurring, outlier enlargement and foreground objects merging to background, etc. The approach we exploited is to segment the image in three scales' superpixels from dense to sparse ones according to downsampling scale first, then compute disparity directly on superpixel's stereo matching. The post-processing of region constraint and local refinement uses hierarchical multi-scale superpixels as well. The proposed approach is validated on Middle-bury test-bed, and the experimental results outperform the current state-of-the-art stereo matching methods in low resolutions.

    Original languageEnglish
    Title of host publication2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
    Pages5046-5049
    Number of pages4
    DOIs
    Publication statusPublished - 2010
    Event2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 - Buenos Aires, Argentina
    Duration: 31 Aug 20104 Sept 2010

    Publication series

    Name2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10

    Conference

    Conference2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
    Country/TerritoryArgentina
    CityBuenos Aires
    Period31/08/104/09/10

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