Surface Registration by Optimization in Constrained Diffeomorphism Space

Wei Zeng, Lok Ming Lui, Xianfeng Gu; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014, pp. 4169-4176

Abstract


This work proposes a novel framework for optimization in the constrained diffeomorphism space for deformable surface registration. First the diffeomorphism space is modeled as a special complex functional space on the source surface, the Beltrami coefficient space. The physically plausible constraints, in terms of feature landmarks and deformation types, define subspaces in the Beltrami coefficient space. Then the harmonic energy of the registration is minimized in the constrained subspaces. The minimization is achieved by alternating two steps: 1) optimization - diffuse the Beltrami coefficient, and 2) projection - first deform the conformal structure by the current Beltrami coefficient and then compose with a harmonic map from the deformed conformal structure to the target. The registration result is diffeomorphic, satisfies the physical landmark and deformation constraints, and minimizes the conformality distortion. Experiments on human facial surfaces demonstrate the efficiency and efficacy of the proposed registration framework.

Related Material


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[bibtex]
@InProceedings{Zeng_2014_CVPR,
author = {Zeng, Wei and Ming Lui, Lok and Gu, Xianfeng},
title = {Surface Registration by Optimization in Constrained Diffeomorphism Space},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2014}
}