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BADF: Bounding Volume Hierarchies Centric Adaptive Distance Field Computation for Deformable Objects on GPUs

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Abstract

We present a novel algorithm BADF (Bounding Volume Hierarchy Based Adaptive Distance Fields) for accelerating the construction of ADFs (adaptive distance fields) of rigid and deformable models on graphics processing units. Our approach is based on constructing a bounding volume hierarchy (BVH) and we use that hierarchy to generate an octree-based ADF. We exploit the coherence between successive frames and sort the grid points of the octree to accelerate the computation. Our approach is applicable to rigid and deformable models. Our GPU-based (graphics processing unit based) algorithm is about 20x–50x faster than current mainstream central processing unit based algorithms. Our BADF algorithm can construct the distance fields for deformable models with 60k triangles at interactive rates on an NVIDIA GTX GeForce 1060. Moreover, we observe 3x speedup over prior GPU-based ADF algorithms.

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Authors and Affiliations

  1. Laboratory of Geometry, Image and Video Processing Enterprise Intelligent Computing, College of Computer Science and Technology, Zhejiang University, Hangzhou, 310007, China

    Xiao-Rui Chen, Min Tang, Cheng Li & Ruo-Feng Tong

  2. Geometric Algorithms for Modeling, Motion, and Animation Laboratory, University of Maryland, College Park, Maryland, 20742, USA

    Dinesh Manocha

Authors
  1. Xiao-Rui Chen
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  2. Min Tang
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  3. Cheng Li
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  4. Dinesh Manocha
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  5. Ruo-Feng Tong
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Correspondence to Xiao-Rui Chen.

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Chen, XR., Tang, M., Li, C. et al. BADF: Bounding Volume Hierarchies Centric Adaptive Distance Field Computation for Deformable Objects on GPUs. J. Comput. Sci. Technol. 37, 731–740 (2022). https://doi.org/10.1007/s11390-022-0331-x

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