Three-dimensional mapping utilizing stereo vision and Bayesian inference

Tatsunori Kou, Kenji Suzuki, Shuji Hashimoto

    研究成果: Conference contribution

    2 被引用数 (Scopus)


    In this study we propose a method for creating 3D map of real world environment by using 3D occupancy grids. The map is created by characterizing each grid associated with a certain area in the real world environment by utilizing multiple measurements using stereo vision and Bayesian inference. The proposed method can absorb the measurement uncertainties caused in the stereo matching process and in the system's calibrations. The preliminary experiments show that the proposed algorithm is able to robustly generate environment maps. The algorithm is also suitable to be implemented as a vision system for autonomous mobile robots.

    ホスト出版物のタイトルProceedings of SPIE - The International Society for Optical Engineering
    編集者S. Kaneko, H. Cho, G.K. Knopf, R. Tutsch
    出版ステータスPublished - 2004
    イベントMachine Vision and its Optomechatronic Applications - Philadelphia, PA, United States
    継続期間: 2004 10 262004 10 28


    OtherMachine Vision and its Optomechatronic Applications
    CountryUnited States
    CityPhiladelphia, PA

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering
    • Condensed Matter Physics

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