TRPLP – Trifocal Relative Pose From Lines at Points
TRPLP – Trifocal Relative Pose From Lines at Points
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DOI：
10.1109/cvpr42600.2020.01209
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发表时间：
2020-06
期刊：
影响因子：
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通讯作者：
R. Fabbri;Timothy Duff;Hongyi Fan;Margaret H. Regan;David da Costa de Pinho;Elias P. Tsigaridas;C. Wam
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文献类型：
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作者：
R. Fabbri;Timothy Duff;Hongyi Fan;Margaret H. Regan;David da Costa de Pinho;Elias P. Tsigaridas;C. Wam
我们提出了一种方法来解决两个最小问题的相对摄像机姿态估计从三个视图，这是基于三个视图对应的（i）三点和一条线和（ii）三点和两条线通过两个点。这些问题是太困难了，有效地解决了现有的Grobner基方法。我们的方法是基于一个新的高效同伦连续（HC）求解器，这大大加快了以前的HC解决专门HC方法，我们的问题的一般情况下。我们在模拟实验中表明，我们的求解器是数字鲁棒性和稳定的图像噪声下。我们在真实的实验中表明，（i）SIFT特征为三视图重建提供了足够好的点和线对应关系，（ii）我们可以解决困难的情况下，太少或太嘈杂的试探性匹配，其中来自运动初始化的最先进的结构失败。
We present a method for solving two minimal problems for relative camera pose estimation from three views, which are based on three view correspondences of (i) three points and one line and (ii) three points and two lines through two of the points. These problems are too difficult to be efficiently solved by the state of the art Grobner basis methods. Our method is based on a new efficient homotopy continuation (HC) solver, which dramatically speeds up previous HC solving by specializing HC methods to generic cases of our problems. We show in simulated experiments that our solvers are numerically robust and stable under image noise. We show in real experiment that (i) SIFT features provide good enough point-and-line correspondences for three-view reconstruction and (ii) that we can solve difficult cases with too few or too noisy tentative matches where the state of the art structure from motion initialization fails.