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

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 w...

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Bibliographic Details
Published in:Journal of computer science and technology 2022-06, Vol.37 (3), p.731-740
Main Authors: Chen, Xiao-Rui, Tang, Min, Li, Cheng, Manocha, Dinesh, Tong, Ruo-Feng
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Artificial Intelligence
Central processing units
Computation
Computer Science
Construction
CPUs
Data Structures and Information Theory
Deformation
Formability
Graphics processing units
Hierarchies
Information Systems Applications (incl.Internet)
Microprocessors
Octrees
Queries
Regular Paper
Software Engineering
Theory of Computation
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Summary: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.
ISSN:1000-9000
1860-4749
DOI:10.1007/s11390-022-0331-x