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3D Reconstruction by a Mobile Robot using Multi-Baseline Omni-Directional Motion Stereo based on GPS/DR Compound Navigation System

机译:基于GPS / DR复合导航系统的多基线全向运动立体声的移动机器人三维重建

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In this paper, a unique dense 3D shape reconstruction method featuring GPS/DR coupled omni-direction multi-baseline motion stereo system is presented. The epipolar plane equation between two Omni Directional Vision images is computed from the GPS/DR's position and posture information. Then, the precise epipolar lines can be obtained robustly by projecting the intersection line between the epipolar plane and the ODV's image plane. The robust matching method featuring hybrid use of the future based matching and the area based matching, as well as the bi-directional matching which chose common mutual matching points to improve robustness is also presented. Voting process using multi-baseline is used to reduce distance error of motion stereo. Hundreds of dense range images are unified based on the precise position/posture information to generate the successive dense 3D outdoor model. The range estimation accuracy within 10 [m] area is 140 [mm], which is equal to a laser radar. It can be said that the proposed omni-directional stereo vision has robustness toward environmental complication and accurate distance estimation performance for rich textured object.
机译:本文介绍了一种独特的致密3D形重建方法,呈现了GPS / DR耦合全方向多基线运动立体声系统。两个Omni定向视觉图像之间的骨头平面方程从GPS / DR的位置和姿势信息计算。然后,通过突出ePIPOL平面和ODV的图像平面之间的交叉线来稳健地获得精确的末端线。还呈现了具有混合使用基于匹配和基于区域的匹配的鲁棒匹配方法以及选择普通相互匹配点以改善鲁棒性的双向匹配。使用多基线的投票过程用于减少运动立体声的距离误差。基于精确的位置/姿势信息统一数百个密集范围图像,以产生连续致密的3D室外模型。 10 [M]区域内的范围估计精度为140 [mm],其等于激光雷达。可以说,所提出的全定向立体声视力对环境并发症具有稳健性,以及富纹理对象的准确距离估计性能。

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