Three-Dimensional Reconstruction of Points and Lines with Unknown Correspondence across Images
International Journal of Computer Vision
Indoor scene reconstruction from sets of noisy range images
3DIM'99 Proceedings of the 2nd international conference on 3-D digital imaging and modeling
Visual motion capturing for kinematic model estimation of a humanoid robot
DAGM'11 Proceedings of the 33rd international conference on Pattern recognition
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This paper addresses the general 3-D rigid motion problem, where the point correspondences and the motion parameters between two sets of 3-D points are to be recovered. The existence of missing points in the two sets is the most difficult problem. We first show a mathematical symmetry in the solutions of rotation parameters and point correspondences. A closed-form solution based on the correlation matrix eigenstructure decomposition is proposed for correspondence recovery with no missing points. Using a heuristic measure of point pair affinity derived from the eigenstructure, a weighted bipartite matching algorithm is developed to determine the correspondences in general cases where missing points occur. The use of the affinity heuristic also leads to a fast outlier removal algorithm, which can be run iteratively to refine the correspondence recovery. Simulation results and experiments on real images are shown in both ideal and general cases.