Factoring Algebraic Error for Relative Pose Estimation

Lindstrom, P ; Duchaineau, M

Lawrence Livermore National Laboratory

关键词: Eigenvectors;    Cameras;    Functionals;    Factorization;    99 General And Miscellaneous;   

DOI  :  10.2172/983382
RP-ID  :  LLNL-TR-411194
RP-ID  :  W-7405-ENG-48
RP-ID  :  983382

美国|英语

来源: UNT Digital Library

【 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.