New Algorithms for 2D and 3D Point Matching: Pose Estimation and Correspondence

Part of Advances in Neural Information Processing Systems 7 (NIPS 1994)

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Steven Gold, Chien-Ping Lu, Anand Rangarajan, Suguna Pappu, Eric Mjolsness


A fundamental open problem in computer vision-determining pose and correspondence between two sets of points in space(cid:173) is solved with a novel, robust and easily implementable algorithm. The technique works on noisy point sets that may be of unequal sizes and may differ by non-rigid transformations. A 2D varia(cid:173) tion calculates the pose between point sets related by an affine transformation-translation, rotation, scale and shear. A 3D to 3D variation calculates translation and rotation. An objective describ(cid:173) ing the problem is derived from Mean field theory. The objective is minimized with clocked (EM-like) dynamics. Experiments with both handwritten and synthetic data provide empirical evidence for the method.