Triangle Mesh-Based Edge Detection And Its Application To Surface Segmentation And Adaptive Surface Smoothing (2002) [5 citations — 0 self]
Abstract:
Triangle meshes are widely used in representing surfaces in computer vision and computer graphics. Although 2D image processingbased edge detection techniques have been popular in many application areas, they are not well developed for surfaces represented by triangle meshes. This paper proposes a robust edge detection algorithm for triangle meshes and its applications to surface segmentation and adaptive surface smoothing. The proposed edge detection technique is based on eigen analysis of the surface normal vector field in a geodesic window. To compute the edge strength of a certain vertex, the neighboring vertices in a specified geodesic distance are involved. Edge information are used further to segment the surfaces with watershed algorithm and to achieve edgepreserved, adaptive surface smoothing. The proposed algorithm is novel in robustly detecting edges on triangle meshes against noise. The 3D watershed algorithm is an extension from previous work. Experimental results on surfaces reconstructed from multi-view real range images are presented. 1.
Citations
| 352 | A signal processing approach to fair surface design – Taubin - 1995 |
| 151 | Set Methods and Fast Marching Methods: Evolving – Level - 1999 |
| 86 | Computing geodesic paths on manifolds – Kimmel, Sethian - 1998 |
| 71 | Partitioning 3D surface meshes using watershed segmentation – Mangan, Whitaker - 1999 |
| 57 | The watershed transform: definitions, algorithms, and parallellization strategies – Roerdink, Meijster |
| 26 | Polyhedral surface smoothing with simultaneous mesh regularization – Ohtake, Belyaev, et al. - 2000 |
| 24 | 3d part segmentation using simulated electrical charge distributions – Wu, Levine - 1997 |
| 15 | Robust crease detection and curvature estimation of piecewise smooth surfaces from triangle mesh approximations using normal voting – Page, Koschan, et al. - 2001 |
| 13 | Surface matching by 3d point’s fingerprint – Sun, Abidi - 2001 |
| 3 | A Computational Framework for Segmentation and – Medioni, Lee, et al. - 2000 |
