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A modified iterative closest point algorithm for shape registration
Author(s): Dmitrii Tihonkih; Artyom Makovetskii; Vladislav Kuznetsov
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Paper Abstract

The iterative closest point (ICP) algorithm is one of the most popular approaches to shape registration. The algorithm starts with two point clouds and an initial guess for a relative rigid-body transformation between them. Then it iteratively refines the transformation by generating pairs of corresponding points in the clouds and by minimizing a chosen error metric. In this work, we focus on accuracy of the ICP algorithm. An important stage of the ICP algorithm is the searching of nearest neighbors. We propose to utilize for this purpose geometrically similar groups of points. Groups of points of the first cloud, that have no similar groups in the second cloud, are not considered in further error minimization. To minimize errors, the class of affine transformations is used. The transformations are not rigid in contrast to the classical approach. This approach allows us to get a precise solution for transformations such as rotation, translation vector and scaling. With the help of computer simulation, the proposed method is compared with common nearest neighbor search algorithms for shape registration.

Paper Details

Date Published: 28 September 2016
PDF: 8 pages
Proc. SPIE 9971, Applications of Digital Image Processing XXXIX, 99712D (28 September 2016); doi: 10.1117/12.2237911
Show Author Affiliations
Dmitrii Tihonkih, Chelyabinsk State Univ. (Russian Federation)
Artyom Makovetskii, Chelyabinsk State Univ. (Russian Federation)
Vladislav Kuznetsov, Chelyabinsk State Univ. (Russian Federation)


Published in SPIE Proceedings Vol. 9971:
Applications of Digital Image Processing XXXIX
Andrew G. Tescher, Editor(s)

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