兰萨克
姿势
估计员
计算机科学
迭代最近点
NIST公司
基本事实
迭代法
点(几何)
人工智能
方案(数学)
算法
三维姿态估计
计算机视觉
数学
图像(数学)
点云
统计
自然语言处理
数学分析
几何学
作者
Johan Hedborg,Michael Felsberg
标识
DOI:10.1109/worv.2013.6521915
摘要
Robust estimation of the relative pose between two cameras is a fundamental part of Structure and Motion methods. For calibrated cameras, the five point method together with a robust estimator such as RANSAC gives the best result in most cases. The current state-of-the-art method for solving the relative pose problem from five points is due to Nistér [9], because it is faster than other methods and in the RANSAC scheme one can improve precision by increasing the number of iterations. In this paper, we propose a new iterative method, which is based on Powell's Dog Leg algorithm. The new method has the same precision and is approximately twice as fast as Nister's algorithm. The proposed method is easily extended to more than five points while retaining a efficient error metrics. This makes it also very suitable as an refinement step. The proposed algorithm is systematically evaluated on three types of datasets with known ground truth.
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