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Surface and Curve Skeletonization of Large 3D Models on the GPU
June 2013 (vol. 35 no. 6)
pp. 1495-1508
Andrei C. Jalba, Eindhoven University of Technology, Eindhoven
Jacek Kustra, Philips Research, Eindhoven
Alexandru C. Telea, University of Groningen, Groningen
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.
Index Terms:
Skeleton,Shape,Graphics processing unit,Surface reconstruction,Image reconstruction,Timing,skeleton regularization,Medial axes,geodesics
Andrei C. Jalba, Jacek Kustra, Alexandru C. Telea, "Surface and Curve Skeletonization of Large 3D Models on the GPU," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 35, no. 6, pp. 1495-1508, June 2013, doi:10.1109/TPAMI.2012.212
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