Robust 3-dimensional object recognition using stereo vision and geometric hashing

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    Abstract

    We propose a technique that combines geometric hashing with stereo vision. The idea is to use the robustness of geometric hashing to spurious data to overcome the correspondence problem, while the stereo vision setup enables direct model matching using the 3-D object models. Furthermore, because the matching technique relies on the relative positions of local features, we should be able to perform robust recognition even with partially occluded objects. We tested this approach with simple geometric objects using a corner point detector. We successfully recognized objects even in scenes where the objects were partially occluded by other objects. For complicated scenes, however, the limited set of model features and required amount of computing time, sometimes became a problem
    Original languageEnglish
    Title of host publicationProceedings of the 3rd IEEE International Conference on Image Processing, ICIP 1996
    Place of PublicationPiscataway, NJ
    PublisherIEEE
    Pages329-332
    Number of pages4
    ISBN (Print)0-7803-3672-0
    DOIs
    Publication statusPublished - 1996
    Event3rd IEEE International Conference on Image Processing, ICIP 1996 - Lausanne, Switzerland
    Duration: 16 Sep 199619 Sep 1996
    Conference number: 3

    Conference

    Conference3rd IEEE International Conference on Image Processing, ICIP 1996
    Abbreviated titleICIP
    CountrySwitzerland
    CityLausanne
    Period16/09/9619/09/96

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