Learning Boundary Edges for 3D‐Mesh Segmentation
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Date
2011
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and Blackwell Publishing Ltd.
Abstract
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.
Description
@article{:10.1111/j.1467-8659.2011.01967.x,
journal = {Computer Graphics Forum},
title = {{Learning Boundary Edges for 3D‐Mesh Segmentation}},
author = {Benhabiles, Halim and Lavoué, Guillaume and Vandeborre, Jean‐Philippe and Daoudi, Mohamed},
year = {2011},
publisher = {The Eurographics Association and Blackwell Publishing Ltd.},
ISSN = {1467-8659},
DOI = {/10.1111/j.1467-8659.2011.01967.x}
}