TY - GEN
T1 - Registration for 3D surfaces with large deformations using quasi-conformal curvature flow
AU - Zeng, Wei
AU - Gu, Xianfeng David
PY - 2011
Y1 - 2011
N2 - A novel method for registering 3D surfaces with large deformations is presented, which is based on quasi-conformal geometry. A general diffeomorphism distorts the conformal structure of the surface, which is represented as the Beltrami coefficient. Inversely, the diffeomorphism can be determined by the Beltrami coefficient in an essentially unique way. Our registration method first extracts the features on the surfaces, then estimates the Beltrami coefficient, and finally uniquely determines the registration mapping by solving Beltrami equations using curvature flow. The method is 1) general, it can search the desired registration in the whole space of diffeomorphisms, which includes the conventional searching spaces, such as rigid motions, isometric transformations or conformal mappings; 2) global optimal, the global optimum is determined by the method unique up to a 3 dimensional transformation group; 3) robust, it handles large surfaces with complicated topologies; 4) rigorous, it has solid theoretic foundation. Experiments on the real surfaces with large deformations and complicated topologies demonstrate the efficiency, robustness of the proposed method.
AB - A novel method for registering 3D surfaces with large deformations is presented, which is based on quasi-conformal geometry. A general diffeomorphism distorts the conformal structure of the surface, which is represented as the Beltrami coefficient. Inversely, the diffeomorphism can be determined by the Beltrami coefficient in an essentially unique way. Our registration method first extracts the features on the surfaces, then estimates the Beltrami coefficient, and finally uniquely determines the registration mapping by solving Beltrami equations using curvature flow. The method is 1) general, it can search the desired registration in the whole space of diffeomorphisms, which includes the conventional searching spaces, such as rigid motions, isometric transformations or conformal mappings; 2) global optimal, the global optimum is determined by the method unique up to a 3 dimensional transformation group; 3) robust, it handles large surfaces with complicated topologies; 4) rigorous, it has solid theoretic foundation. Experiments on the real surfaces with large deformations and complicated topologies demonstrate the efficiency, robustness of the proposed method.
UR - https://www.scopus.com/pages/publications/80052870745
U2 - 10.1109/CVPR.2011.5995410
DO - 10.1109/CVPR.2011.5995410
M3 - Conference contribution
AN - SCOPUS:80052870745
SN - 9781457703942
T3 - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
SP - 2457
EP - 2464
BT - 2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011
PB - IEEE Computer Society
ER -