Invariant surface characteristics for 3D object recognition in range images
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We propose a method for coarse registration of multiple range images that uses a log-polar height map (LPHM) as the key for establishing correspondence. The LPHM is a local height map orthogonally mapped on the tangent plane with the log-polar coordinate system. The input range images are roughly represented by signed distance field (SDF) samples. For each SDF sample, an LPHM is generated and is converted to an invariant feature vector. Point correspondence is established by a nearest neighbor search in feature space. The RANSAC algorithm is applied on the corresponding point pairs between each pair of range images, and the pairwise registration of input range images is determined by the extracted inlier point pairs. Finally, the global registration is determined by constructing a view tree, which is the spanning tree that maximizes the total number of inlier point pairs. The result of coarse registration is used as the initial state of the fine registration and modeling. The proposed method was tested on multiple real range image datasets.