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Mesh Segmentation for Parallel Decompression on GPU

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNIP,volume 7633)

Abstract

We present a novel algorithm to partition large 3D meshes for GPU-based decompression. Our formulation focuses on minimizing the replicated vertices between patches, and balancing the numbers of faces of patches for efficient parallel computing. First we generate a topology model of the original mesh and remove vertex positions. Then we assign the centers of patches using geodesic farthest point sampling and cluster the faces according to geodesic distance. After the segmentation we swap boundary faces to fix jagged boundaries and store the boundary vertices for whole-mesh preservation. The decompression of each patch runs on a thread of GPU, we have evaluated its performance on various large benchmarks. In practice, the GPU-based decompression algorithm runs more than 48X faster with that on the CPU.

Keywords

  • Parallel decompression
  • Mesh segmentation
  • Connectivity compression
  • GPU
  • Edgebreaker

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© 2012 Springer-Verlag Berlin Heidelberg

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Zhao, J., Tang, M., Tong, R. (2012). Mesh Segmentation for Parallel Decompression on GPU. In: Hu, SM., Martin, R.R. (eds) Computational Visual Media. CVM 2012. Lecture Notes in Computer Science, vol 7633. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34263-9_11

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  • DOI: https://doi.org/10.1007/978-3-642-34263-9_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34262-2

  • Online ISBN: 978-3-642-34263-9

  • eBook Packages: Computer ScienceComputer Science (R0)