Surface and curve skeletonization of large 3D models on the GPU

A.C. Jalba, J. Kustra, A.C. Telea

Research output: Contribution to journalArticleAcademicpeer-review

49 Citations (Scopus)


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 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. Keywords: Medial axes, geodesics, skeleton regularization
Original languageEnglish
Pages (from-to)1495-1508
Number of pages14
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Issue number6
Publication statusPublished - 2013


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