| Literature DB >> 23599061 |
Andrei C Jalba1, Jacek Kustra, Alexandru C Telea.
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.Mesh:
Year: 2013 PMID: 23599061 DOI: 10.1109/TPAMI.2012.212
Source DB: PubMed Journal: IEEE Trans Pattern Anal Mach Intell ISSN: 0098-5589 Impact factor: 6.226