Factoring Algebraic Error for Relative Pose Estimation

Lindstrom, P ; Duchaineau, M

关键词: ALGORITHMS;    CAMERAS;    EIGENVECTORS;    FACTORIZATION;    FUNCTIONALS;    OPTIMIZATION;    ROTATION;   

DOI  :  10.2172/983382
RP-ID  :  LLNL-TR-411194
PID  :  OSTI ID: 983382
Others  :  TRN: US201014%%637

学科分类：社会科学、人文和艺术（综合）

美国|英语

来源: SciTech Connect

【 摘 要 】

We address the problem of estimating the relative pose, i.e. translation and rotation, of two calibrated cameras from image point correspondences. Our approach is to factor the nonlinear algebraic pose error functional into translational and rotational components, and to optimize translation and rotation independently. This factorization admits subproblems that can be solved using direct methods with practical guarantees on global optimality. That is, for a given translation, the corresponding optimal rotation can directly be determined, and vice versa. We show that these subproblems are equivalent to computing the least eigenvector of second- and fourth-order symmetric tensors. When neither translation or rotation is known, alternating translation and rotation optimization leads to a simple, efficient, and robust algorithm for pose estimation that improves on the well-known 5- and 8-point methods.