NDLI: Fast parallel computation of shape diameter function

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Fast parallel computation of shape diameter function

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Fast parallel computation of shape diameter function

Content Provider	ACM Digital Library
Author	Baldacci, Andrea Riečický, Adam Cignoni, Paolo Ďurikovič, Roman Madaras, Martin Kamenický, Rastislav Scopigno, Roberto
Abstract	We outline and compare two approaches for the computation of the shape diameter function (SDF) on the GPU. The SDF is a scalar function describing the local thickness of an object. It can be used for consistent mesh partitioning and skeletonization. In the first approach, we have reorganized the tracing of rays to be well suited for the rasterization hardware. To the best of our knowledge, this is the first method to show how to compute the SDF using only the rasterization hardware and without the need of any acceleration data structures. The second approach uses parallel ray casting and octree traversal using OpenCL. We demonstrate that first method achieves similar results as the ray casting using OpenCL, it is faster for large meshes and it simpler to implement. Furthermore, we extend the SDF computation by fast post-processing using texture-space diffusion. Fast SDF computation can be use in many applications such as automatic skeleton extraction demonstrated in the article.
Starting Page	5
Ending Page	5
Page Count	1
File Format	PDF
ISBN	9781450344364
DOI	10.1145/2948628.2948634
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-04-27
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Shape diameter function Skeleton extraction Depth peeling Opencl Gpu Stm
Content Type	Text
Resource Type	Article

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