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Rigid Body Pose Estimation from Line Correspondences

机译:刚性体姿态估计从线路相应

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In this paper, we aim to solve pose estimation of rigid body motion in real time with 3d lines model. According to the line's perspective projection model, we design a new error function expressed by the average integral of the distance between line segments to estimate parameters. Considering the continuely of motion, we restore cracked line segements with re-projection of Model lines Constrianted. Last, we proposal to estimate many frames jointly in framework of SFM and get better precious while bears slow speed. Comparisons on synthetic and real images demonstrate that baseline methods get accuracy estimations in complex environments. For plane objects, the precious of pose on x, y, z axes are better than 0.5m in 100m distance, and those of relative positions perpendicular to the optical axis and along the optical axis are better than 0.3%.
机译:在本文中,我们的目标是与3D线模型实时解决刚体运动的姿势估计。根据线的透视投影模型,我们设计了一个新的错误函数,由线段之间的距离的平均积分表示以估计参数。考虑到持续的运动,我们通过重新投影恢复裂纹的线路段,用于重新投影模型线。最后,我们提出在SFM框架中估计许多帧,并获得更好的珍贵,而持续速度。合成和实图像的比较表明基线方法在复杂环境中获得精度估计。对于平面物体,X,Y,Z轴上的珍贵姿势在100米处优于0.5米,并且垂直于光轴和沿光轴的相对位置的比较优于0.3%。

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