Robust optical flow estimation of double-layer images under transparency or reflection

Jiaolong Yang, Hongdong Li, Yuchao Dai, Robby T. Tan

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

    42 Citations (Scopus)

    Abstract

    This paper deals with a challenging, frequently encountered, yet not properly investigated problem in two-frame optical flow estimation. That is, the input frames are compounds of two imaging layers - one desired background layer of the scene, and one distracting, possibly moving layer due to transparency or reflection. In this situation, the conventional brightness constancy constraint - the cornerstone of most existing optical flow methods - will no longer be valid. In this paper, we propose a robust solution to this problem. The proposed method performs both optical flow estimation, and image layer separation. It exploits a generalized double-layer brightness consistency constraint connecting these two tasks, and utilizes the priors for both of them. Experiments on both synthetic data and real images have confirmed the efficacy of the proposed method. To the best of our knowledge, this is the first attempt towards handling generic optical flow fields of two-frame images containing transparency or reflection.

    Original languageEnglish
    Title of host publicationProceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016
    PublisherIEEE Computer Society
    Pages1410-1419
    Number of pages10
    ISBN (Electronic)9781467388504
    DOIs
    Publication statusPublished - 9 Dec 2016
    Event29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016 - Las Vegas, United States
    Duration: 26 Jun 20161 Jul 2016

    Publication series

    NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
    Volume2016-December
    ISSN (Print)1063-6919

    Conference

    Conference29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016
    Country/TerritoryUnited States
    CityLas Vegas
    Period26/06/161/07/16

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