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Topology-preserving nonlinear shape registration on the shape manifold

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Abstract

Shape registration is a vital task in computer vision and image processing, but the topology changes always occur in registration process of two shapes with large deformation. In this paper, we address the shape registration with large deformation by an atlas based method. Concretely, we first represent the shape by the square root velocity functions (SRVFs) which makes registration of two shapes with small deformation well. Then, we hierarchically cluster all shapes and form a clustering tree under this representation. Further, by searching the shortest path connecting two shapes we realize the registration with topology preserving. Finally, the numerical results on the Kimia shape dataset show that our proposed method achieves a better performance of registration than the conventional method. That is, the atlas-based strategy is valid for shape registration with large deformation.

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  1. http://www.lems.brown.edu/vision/researchAreas/SIID/.

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Authors and Affiliations

  1. Department of Mathematics, School of Sciences, Shanghai University, Shanghai, 200444, People’s Republic of China

    Lei Jin & Zhijie Wen

  2. Intelligent Information Systems Institute, Wenzhou University, Wenzhou, Zhejiang, 325035, People’s Republic of China

    Zhongyi Hu

Authors
  1. Lei Jin
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  2. Zhijie Wen
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  3. Zhongyi Hu
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Correspondence to Zhongyi Hu.

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This research is supported by the National Natural Science Foundation of China under Grants 11971296, 11701357, U1809209, the Capacity Construction Project of Local Universities in Shanghai under Grant 18010500600, and the Major Project of Wenzhou Natural Science Foundation under Grant ZY2019020.

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Jin, L., Wen, Z. & Hu, Z. Topology-preserving nonlinear shape registration on the shape manifold. Multimed Tools Appl 80, 17377–17389 (2021). https://doi.org/10.1007/s11042-020-09203-y

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  • DOI: https://doi.org/10.1007/s11042-020-09203-y

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