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Dynamic programming for multi-view disparity/depth estimation

    Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

    17 Citations (Scopus)
    358 Downloads (Pure)

    Abstract

    A novel algorithm for disparity/depth estimation from multi-view images is presented. A dynamic programming approach with window-based correlation and a novel cost function is proposed. The smoothness of disparity/depth map is embedded in dynamic programming approach, whilst the window-based correlation increases reliability. The enhancement methods are included, i.e. adaptive window size and shiftable window are used to increase reliability in homogenous areas and to increase sharpness at object boundaries. First, the algorithms estimate depth maps along a single camera axis. The algorithms exploits then combines the depth estimates from different axis to derive a suitable depth map for multi-view images. The proposed scheme outperforms existing approaches in parallel and in the non-parallel camera configurations
    Translated title of the contributionDynamic programming for multi-view disparity/depth estimation
    Original languageEnglish
    Title of host publication2006 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006) Toulouse, France
    PublisherInstitute of Electrical and Electronics Engineers (IEEE)
    Pages269 - 272
    Number of pages4
    Volume2
    ISBN (Print)142440469X
    DOIs
    Publication statusPublished - May 2006
    Event2006 IEEE International Conference on Acoustics, Speech and Signal Processing - Centre de Congrès Pierre Baudis, Toulouse, France
    Duration: 14 May 2006 → 19 May 2006

    Publication series

    Name
    ISSN (Print)15206149

    Conference

    Conference2006 IEEE International Conference on Acoustics, Speech and Signal Processing
    Abbreviated titleICASSP '06
    Country/TerritoryFrance
    CityToulouse
    Period14/05/06 → 19/05/06

    Bibliographical note

    Rose publication type: Conference contribution

    Terms of use: Copyright © 2006 IEEE. Reprinted from IEEE International Conference on Acoustics, Speech and Signal Processing, 2006 (ICASSP 2006).

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