Learning Boundary Edges for 3D‐Mesh Segmentation
| dc.contributor.author | Benhabiles, Halim | en_US |
| dc.contributor.author | Lavoué, Guillaume | en_US |
| dc.contributor.author | Vandeborre, Jean‐Philippe | en_US |
| dc.contributor.author | Daoudi, Mohamed | en_US |
| dc.contributor.editor | Eduard Groeller and Holly Rushmeier | en_US |
| dc.date.accessioned | 2015-02-27T16:45:30Z | |
| dc.date.available | 2015-02-27T16:45:30Z | |
| dc.date.issued | 2011 | en_US |
| dc.description.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. | en_US |
| dc.description.number | 8 | |
| dc.description.seriesinformation | Computer Graphics Forum | en_US |
| dc.description.volume | 30 | |
| dc.identifier.doi | 10.1111/j.1467-8659.2011.01967.x | en_US |
| dc.identifier.issn | 1467-8659 | en_US |
| dc.identifier.uri | https://doi.org/10.1111/j.1467-8659.2011.01967.x | en_US |
| dc.publisher | The Eurographics Association and Blackwell Publishing Ltd. | en_US |
| dc.title | Learning Boundary Edges for 3D‐Mesh Segmentation | en_US |