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Maximum spatial–temporal isometric cluster for dynamic surface correspondence

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Abstract

Isometric correspondence is an important technique for surface correspondence. Recently, numerous algorithms have been proposed to build isometric mapping. However, those methods tend to be error prone due to the topological variation and noises of the dynamic surface. To address this issue, we propose a dynamic surface correspondence method by computing maximum spatial–temporal isometric cluster. Firstly, the algorithm defines a maximum isometric cluster score to measure the correspondence quality of each cluster in the product space. Then, the maximum problem is formulated into a quadratic programming problem. Furthermore, we define a similarity function which explicitly encodes the spatial–temporal consistence of the dynamic surface. It can greatly reduce the solving dimension, and improve the correspondence accuracy. Finally, the result is extended to the dense correspondence by a geodesic distance vector. Experimental results show that our algorithm can generate consistent correspondence on three databases of surface sequences, which outperforms existing state-of-the-art algorithms.

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Acknowledgements

This research work was supported by China Natural Science Foundation (Grant No: 61502133). Part of the work is supported by Natural Science Foundation of Zhejiang Province (Grant Nos: LY19F020031, LY16F020029).The authors also thank the anonymous reviewers for their kind comments.

Funding

This study was funded by National Natural Science Foundation of China (Grant No.: 61502133).

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Authors and Affiliations

  1. Department of Computer Science, Zhejiang University of Technology, Hangzhou, China

    Xiang Pan & Zhihao Cheng

  2. Hangzhou Institute of Service Engineering, Hangzhou Normal University, Hangzhou, China

    Fuchang Liu

  3. Department of Computer Science, Zhejiang University, Hangzhou, China

    Sanyuan Zhang

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  1. Xiang Pan
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  2. Zhihao Cheng
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  3. Fuchang Liu
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  4. Sanyuan Zhang
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Correspondence to Fuchang Liu.

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Pan, X., Cheng, Z., Liu, F. et al. Maximum spatial–temporal isometric cluster for dynamic surface correspondence. Vis Comput 36, 785–798 (2020). https://doi.org/10.1007/s00371-019-01655-0

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