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Pixel Club: Diffusion-geometric Maximally Stable Component Detection in Deformable Shapes
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Roee Litman (Tel Aviv University)
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Tuesday, 17.5.2011, 11:30
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Room 337-8 Taub Bld.
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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