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arXiv · 1012.3951

Diffusion-geometric maximally stable component detection in deformable shapes

Roee Litman·Alex M. Bronstein·Michael M. Bronstein
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Abstract

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.

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Roee Litman, Alex M. Bronstein, Michael M. Bronstein. 2010-12-17. Diffusion-geometric maximally stable component detection in deformable shapes. https://doi.org/10.1016/j.cag.2011.03.011

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