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25 October 2004 Three-dimensional mapping utilizing stereovision and Bayesian inference
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Proceedings Volume 5603, Machine Vision and its Optomechatronic Applications; (2004)
Event: Optics East, 2004, Philadelphia, Pennsylvania, United States
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.
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Tatsunori Kou, Kenji Suzuki, and Shuji Hashimoto "Three-dimensional mapping utilizing stereovision and Bayesian inference", Proc. SPIE 5603, Machine Vision and its Optomechatronic Applications, (25 October 2004);

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