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Journal Articles Computer Graphics Forum Year : 2011

Learning Boundary Edges for 3D-Mesh Segmentation


This paper presents a 3D-mesh segmentation algorithm based on a learning approach. A large database of manually segmented 3D-meshes is used to learn a boundary edge function. The function is learned using a classifier which automatically selects from a pool of geometric features the most relevant ones to detect candidate boundary edges. We propose a processing pipeline that produces smooth closed boundaries using this edge function. This pipeline successively selects a set of candidate boundary contours, closes them and optimizes them using a snake movement. Our algorithm was evaluated quantitatively using two different segmentation benchmarks and was shown to outperform most recent algorithms from the state-of-the-art.
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hal-00660740 , version 1 (17-01-2012)



Halim Benhabiles, Guillaume Lavoué, Jean-Philippe Vandeborre, Mohamed Daoudi. Learning Boundary Edges for 3D-Mesh Segmentation. Computer Graphics Forum, 2011, 30 (8), pp.2170-2182. ⟨10.1111/j.1467-8659.2011.01967.x⟩. ⟨hal-00660740⟩
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