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Conservative voxelization

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Abstract

We propose a novel hardware-accelerated voxelization algorithm for polygonal models. Compared with previous approaches, our algorithm has a major advantage that it guarantees the conservative correctness in voxelization: every voxel intersecting the input model is correctly recognized. This property is crucial for applications like collision detection, occlusion culling and visibility processing. We also present an efficient and robust implementation of the algorithm in the GPU. Experiments show that our algorithm has a lower memory consumption than previous approaches and is more efficient when the volume resolution is high. In addition, our algorithm requires no preprocessing and is suitable for voxelizing deformable models.

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Authors and Affiliations

  1. State Key Lab of CAD&CG, Zhejiang University, 310027, Hangzhou, China

    Long Zhang, Wei Chen & Qunsheng Peng

  2. The School of Electrical and Computer Engineering, Purdue University, 465 Northwestern Ave., West Lafayette, 47907, IN, USA

    David S. Ebert

Authors
  1. Long Zhang
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  2. Wei Chen
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  3. David S. Ebert
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  4. Qunsheng Peng
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Correspondence to Wei Chen.

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Zhang, L., Chen, W., Ebert, D. et al. Conservative voxelization . Visual Comput 23, 783–792 (2007). https://doi.org/10.1007/s00371-007-0149-0

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  • DOI: https://doi.org/10.1007/s00371-007-0149-0

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