A regularization algorithm for registration of deformable surfaces

Sergei Voronin; Artyom Makovetskii; Aleksei Voronin; J. Diaz-Escobar

doi:10.1117/12.2321521

17 September 2018 A regularization algorithm for registration of deformable surfaces

Sergei Voronin, Artyom Makovetskii, Aleksei Voronin, J. Diaz-Escobar

Proceedings Volume 10752, Applications of Digital Image Processing XLI; 107522S (2018) https://doi.org/10.1117/12.2321521
Event: SPIE Optical Engineering + Applications, 2018, San Diego, California, United States

Abstract

The registration of two surfaces is finding a geometrical transformation of a template surface to a target surface. The transformation combines the positions of the semantically corresponding points. The transformation can be considered as warping the template onto the target. To choose the most suitable transformation from all possible warps, a registration algorithm must satisfies some constraints on the deformation. This is called regularization of the deformation field. Often use regularization based on minimizing the difference between transformations for different vertices of a surface. The variational functional consists of the several terms. One of them is the functional of the ICP (Iterative Closest Point algorithm) variational subproblem for the point-to-point metric for affine transformations. Other elements of the functional are stiffness and landmark terms. In proposed presentation we use variational functional based on the point-toplane metric for affine transformations. In addition, the use of orthogonal transformations is considered. The proposed algorithm is robust relative to bad initialization and incomplete surfaces. For noiseless and complete data, the registration is one-to-one. With the help of computer simulation, the proposed method is compared with known algorithms for the searching of optimal geometrical transformation.

Citation Download Citation

Sergei Voronin, Artyom Makovetskii, Aleksei Voronin, and J. Diaz-Escobar "A regularization algorithm for registration of deformable surfaces", Proc. SPIE 10752, Applications of Digital Image Processing XLI, 107522S (17 September 2018); https://doi.org/10.1117/12.2321521

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