Resultant Based Incremental Recovery of Camera Pose From Pairwise Matches

Y. Kasten, M. Galun, R. Basri
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引用次数: 13

Abstract

Incremental (online) structure from motion pipelines seek to recover the camera matrix associated with an image I_n given n-1 images, I_1,...,I_n-1, whose camera matrices have already been recovered. In this paper, we introduce a novel solution to the six-point online algorithm to recover the exterior parameters associated with I_n. Our algorithm uses just six corresponding pairs of 2D points, extracted each from I_n and from any of the preceding n-1 images, allowing the recovery of the full six degrees of freedom of the n'th camera, and unlike common methods, does not require tracking feature points in three or more images. Our novel solution is based on constructing a Dixon resultant, yielding a solution method that is both efficient and accurate compared to existing solutions. We further use Bernstein's theorem to prove a tight bound on the number of complex solutions. Our experiments demonstrate the utility of our approach.
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基于结果的相机姿势从成对匹配中增量恢复
增量(在线)结构从运动管道寻求恢复与图像I_n相关联的相机矩阵给定n-1图像,I_1,…,I_n-1,其相机矩阵已经恢复。在本文中,我们引入了一种新的六点在线算法来恢复与I_n相关的外部参数。我们的算法只使用6对对应的2D点,分别从I_n和之前的n-1张图像中提取,允许恢复第n个相机的全部6个自由度,并且与普通方法不同,不需要跟踪三个或更多图像中的特征点。我们的新解决方案基于构建Dixon结,与现有解决方案相比,该解决方案既高效又准确。进一步利用Bernstein定理证明了复解个数的紧界。我们的实验证明了我们方法的实用性。
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