Globally Optimal Pose Estimation from Line Correspondences
Correspondences between 2D lines in an image and 3D lines in the surrounding environment can be exploited to determine the camera’s position and attitude (pose). In this paper, we introduce a novel approach to estimate the camera’s pose by directly solving the corresponding least-squares problem algebraically. Specifically, the optimality conditions of the least-squares problem form a system of polynomial equations, which we efficiently solve through the eigendecomposition of a so-called multiplication matrix. Contrary to existing methods, the proposed algorithm (i) is guaranteed to find the globally optimal estimate in the least-squares sense, (ii) does not require initialization, and (iii) has computational cost only linear in the number of measurements. The superior performance of the proposed algorithm compared to previous approaches is demonstrated through extensive simulations and experiments.
Faraz M. Mirzaei Stergios I. Roumeliotis
Dept. of Computer Science and Engineering,University of Minnesota,USA
国际会议
2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)
上海
英文
5581-5588
2011-05-09（万方平台首次上网日期，不代表论文的发表时间）