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A branch-and-bound algorithm for globally optimal camera pose and focal length

机译:全球最佳相机姿态和焦距的分支定界算法

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摘要

This paper considers the problem of finding the global optimum of the camera rotation, translation and the focal length given a set of 2D-3D point pairs. The global solution is obtained under the I-infinity opti-mality by a branch-and-bound algorithm. To obtain the goal, we firstly extend the previous branch-and-bound formulation and show that the image space error (pixel distance) may be used instead of the angular error. Then, we present that the problem of camera pose plus focal length given the rotation is a quasi-convex problem. This provides a derivation of a novel inequality for the branch-and-bound algorithm for our problem. Finally, experimental results with synthetic and real data are provided.
机译:本文考虑了在给定的一组2D-3D点对的情况下找到相机旋转,平移和焦距的全局最优问题。全局解是通过分支定界算法在I-无穷大下获得的。为了达到这个目的,我们首先扩展了先前的分支定界公式,并表明可以使用图像空间误差(像素距离)代替角度误差。然后,我们提出在给定旋转的情况下相机姿态加上焦距的问题是准凸问题。这为我们的问题的分支定界算法提供了一个新的不等式。最后,提供了具有综合和真实数据的实验结果。

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