Diffusion-geometric maximally stable component detection in deformable shapes

Maximally stable component detection is a very popular method for feature analysis in images, mainly due to its low computation cost and high repeatability. With the recent advance of feature-based methods in geometric shape analysis, there is significant interest in finding analogous approaches in the 3D world. In this paper, we formulate a diffusion-geometric framework for stable component detection in non-rigid 3D shapes, which can be used for geometric feature detection and description. A quantitative evaluation of our method on the SHREC'10 feature detection benchmark shows its potential as a source of high-quality features.

• Publication year

  2010

• Venue

  Computers & graphics

• Publication date

  2010-12-17

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.1016/j.cag.2011.03.011arXiv 1012.3951
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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