Title :
Fast iterative five point relative pose estimation
Author :
Hedborg, J. ; Felsberg, Michael
Author_Institution :
Comput. Vision Lab., Linkoping Univ., Linkoping, Sweden
Abstract :
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.
Keywords :
cameras; image motion analysis; iterative methods; pose estimation; Dog Leg algorithm; RANSAC scheme; calibrated cameras; error metrics; fast iterative five point relative pose estimation; iterative method; motion method; precision improvement; robust relative pose estimation; structure method; Cameras; Equations; Estimation; Mathematical model; Noise level; Tracking; Vectors;
Conference_Titel :
Robot Vision (WORV), 2013 IEEE Workshop on
Conference_Location :
Clearwater Beach, FL
Print_ISBN :
978-1-4673-5646-6
Electronic_ISBN :
978-1-4673-5647-3
DOI :
10.1109/WORV.2013.6521915