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arXiv 2105.04460math.AGcs.CVcs.NAmath.NA
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Galois/monodromy群分解三维重建中的极小问题

Galois/monodromy groups for decomposing minimal problems in 3D reconstruction

Georgia Institute of Technology(佐治亚理工学院);Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague(布拉格捷克理工大学信息学、机器人学与控制论研究所);Duke University(杜克大学)

Timothy Duff, Viktor Korotynskiy, Tomas Pajdla, Margaret H. Regan

摘要:

我们认为伽罗瓦/monodromy组出现在计算机视觉应用中,以期建立更有效的多项式求解器。伽罗瓦/单值群允许我们决定给定问题何时分解为代数子问题,以及它是否具有任何对称性。数值代数几何和计算群论的工具使我们能够将这个框架应用于经典和新颖的重建问题。我们考虑三个经典的情况下-3点绝对姿态,5点相对姿态,和4点单应性估计校准相机-其中的分解和对称性可以自然地理解的伽罗瓦/单值群。然后,我们展示了我们的框架可以应用到新的问题,从绝对和相对姿态估计。例如,我们发现了新的对称性的绝对构成的问题,涉及点和线的功能的混合物。我们还描述了一个问题,估计一对校准的单应性之间的三个图像。对于这个64度的问题,我们可以将其降为16度;后者更好地反映了代数解决问题的内在困难。作为一个副产品,我们获得新的约束兼容的单应性,这可能是独立的利益。

英文摘要:

We consider Galois/monodromy groups arising in computer vision applications, with a view towards building more efficient polynomial solvers. The Galois/monodromy group allows us to decide when a given problem decomposes into algebraic subproblems, and whether or not it has any symmetries. Tools from numerical algebraic geometry and computational group theory allow us to apply this framework to classical and novel reconstruction problems. We consider three classical cases--3-point absolute pose, 5-point relative pose, and 4-point homography estimation for calibrated cameras--where the decomposition and symmetries may be naturally understood in terms of the Galois/monodromy group. We then show how our framework can be applied to novel problems from absolute and relative pose estimation. For instance, we discover new symmetries for absolute pose problems involving mixtures of point and line features. We also describe a problem of estimating a pair of calibrated homographies between three images. For this problem of degree 64, we can reduce the degree to 16; the latter better reflecting the intrinsic difficulty of algebraically solving the problem. As a byproduct, we obtain new constraints on compatible homographies, which may be of independent interest.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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