Name
Abstract | ||
|---|---|---|
We present a GPU-based framework for extracting surface and curve skeletons of 3D shapes represented as large polygonal meshes. We use an efficient parallel search strategy to compute point-cloud skeletons and their distance and feature transforms (FTs) with user-defined precision. We regularize skeletons by a new GPU-based geodesic tracing technique which is orders of magnitude faster and more accurate than comparable techniques. We reconstruct the input surface from skeleton clouds using a fast and accurate image-based method. We also show how to reconstruct the skeletal manifold structure as a polygon mesh and the curve skeleton as a polyline. Compared to recent skeletonization methods, our approach offers two orders of magnitude speed-up, high-precision, and low-memory footprints. We demonstrate our framework on several complex 3D models. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/TPAMI.2012.212 | IEEE Trans. Pattern Anal. Mach. Intell. |
Keywords | Field | DocType |
computer graphics,geodesics,medial axis,skeleton,evolution,algorithms,image reconstruction,surface reconstruction,shape,reconstruction,algorithm | Iterative reconstruction,Surface reconstruction,Computer vision,Polygon,Polygon mesh,Computer science,Medial axis,Skeletonization,Artificial intelligence,Graphics processing unit,Geodesic | Journal |
Volume | Issue | ISSN |
35 | 6 | 0162-8828 |
Citations | PageRank | References |
23 | 0.69 | 47 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrei C. Jalba | 1 | 233 | 16.21 |
| Jacek Kustra | 2 | 36 | 3.59 |
| Alexandru Telea | 3 | 1520 | 107.14 |