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Non-rigid registration in 3D implicit vector space

Cheng, Zhi-Quan, Jiang, Wei, Dang, Gang, Martin, Ralph Robert, Li, Jun, Li, Honghua, Chen, Yin, Wang, Yanzhen, Li, Bao, Xu, Kai and Jin, Shiyao 2010. Non-rigid registration in 3D implicit vector space. Presented at: 12th International Conference on Shape Modeling and Applications, Aix-en-Provence, France, 21-23 June 2010. Published in: Pernot, J.-P., Rossignac, J., Spagnuolo, M., Falcidieno, B. and Véron, P. eds. 2010 Shape Modeling International Conference (SMI), 21-23 June 2010, Aix-en-Provence, France. Los Alamitos, CA: IEEE, pp. 37-46. 10.1109/SMI.2010.21

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We present an implicit approach for pair-wise non-rigid registration of moving and deforming objects. Shapes of interest are implicitly embedded in the 3D implicit vector space. In this implicit embedding space, registration is performed using a global-to-local framework. Firstly, a non-linear optimization functional defined on the vector distance function is used to find the global alignment between shapes. Secondly, an incremental cubic B-spline free form deformation is used to recover the non-rigid transformation parameters. Local non-rigid registration is posed in terms of minimising an energy functional, for which we give a closed-form linear system and solve it using an improved iterative Gauss-Seidel method. Our approach can consistently produce smooth and continuous registration fields, and correctly establish dense one-to-one correspondences. It can naturally deal with both open partial and closed shapes, and imperfect models with gaps and noise, through its use of the implicit vector representation. Experimental results on several datasets demonstrate the robustness of the proposed method.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Uncontrolled Keywords: Non-rigid registration; dense correspondence; global alignment; implicit vector space; vector distance function
Publisher: IEEE
ISBN: 9781424472598
Last Modified: 04 Jun 2017 02:53

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