ISSN 0253-2778

CN 34-1054/N

open
Open AccessOpen Access JUSTC Research Article

Anisotropic surface meshing using locally isometric embedding

Cite this: JUSTC, 2020, 50(12): 1460-1471
https://doi.org/10.3969/j.issn.0253-2778.2020.12.003
Funds: This work is supported by the USTC Research Funds of the Double First-Class Initiative(YD0010002003).
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  • Author Bio:

    LI Huicong: Li Huicong is currently a graduate student under the tutelage of assistant researcher Fu Xiaoming. His research interests focus on computer geometry, computer graphics and digital geometry processing.

  • Corresponding author:

    Fu xiaoming (corresponding author) is an assistant researcher in Graphics & Geometric Computing Laboratory, School of Mathematical Sciences, University of Science and Technology of China (USTC). He received his B. S. and Ph. D. degrees both from University of Science and Technology of China in 2011 and 2016, respectively. His research interests include geometric processing and optimization, CAD/ CAE/ IGA/ Fabrication, VR/ AR/ MR and computer-aided geometric design. His research work can be found at his research website: http:/ / staff. ustc. edu. cn / ~ fuxm/ .

  • Received Date: July 15, 2020
  • Accepted Date: September 05, 2020
  • Published Date: December 29, 2020
  • A novel method for anisotropic surface meshing was proposed. Different from the previous methods using globally conformal embeddings or high-dimensional isometric embeddings, our algorithm is based on the idea of locally isometric embedding. In order to achieve isometric embeddings, the input surface was partitioned into a set of cone patches that are remeshed one by one. First, a patch was parameterized bijectively into a plane, then an anisotropic mesh was generated in the parameterized domain, and finally, the remeshed patch was mapped back to the input surface. To deal with the stitching problem between different patches, the cone patch was made containing the previously unprocessed boundary. Therefore, the triangles near the boundary could be remeshed. The robustness of our method was demonstrated on various complex meshes. Compared to the existing methods, our method is more robust, and contains a smaller approximation error to the input mesh.

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