A Genetic Isometric Shape Correspondence Algorithm with Adaptive Sampling

Date

2018-11-01

Author

Sahillioğlu, Yusuf

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We exploit the permutation creation ability of genetic optimization to find the permutation of one point set that puts it into correspondence with another one. To this end, we provide a genetic algorithm for the 3D shape correspondence problem, which is the main contribution of this article. As another significant contribution, we present an adaptive sampling approach that relocates the matched points based on the currently available correspondence via an alternating optimization. The point sets to be matched are sampled from two isometric (or nearly isometric) shapes. The sparse one-to-one correspondence, i.e., bijection, that we produce is validated both in terms of running time and accuracy in a comprehensive test suite that includes four standard shape benchmarks and state-of-the-art techniques.

Subject Keywords

3D shape correspondence, Isometric shape correspondence, Sparse correspondence, Bijection, Genetic algorithm, Adaptive sampling

URI

https://hdl.handle.net/11511/34570

Journal

ACM TRANSACTIONS ON GRAPHICS

DOI

https://doi.org/10.1145/3243593

Collections

Department of Computer Engineering, Article

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Citation Formats

Y. Sahillioğlu, “A Genetic Isometric Shape Correspondence Algorithm with Adaptive Sampling,” ACM TRANSACTIONS ON GRAPHICS, pp. 0–0, 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/34570.