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@article{ART002826219},
author={Jong-Hyun Kim},
title={Efficient GPU Framework for Adaptive and Continuous Signed Distance Field Construction, and Its Applications},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2022},
volume={27},
number={3},
pages={63-69},
doi={10.9708/jksci.2022.27.03.063}

TY - JOUR
AU - Jong-Hyun Kim
TI - Efficient GPU Framework for Adaptive and Continuous Signed Distance Field Construction, and Its Applications
JO - Journal of The Korea Society of Computer and Information
PY - 2022
VL - 27
IS - 3
PB - The Korean Society Of Computer And Information
SP - 63
EP - 69
SN - 1598-849X
AB - In this paper, we propose a new GPU-based framework for quickly calculating adaptive and continuous SDF(Signed distance fields), and examine cases related to rendering/collision processing using them. The quadtree constructed from the triangle mesh is transferred to the GPU memory, and the Euclidean distance to the triangle is processed in parallel for each thread by using it to find the shortest continuous distance without discontinuity in the adaptive grid space. In this process, it is shown through experiments that the cut-off view of the adaptive distance field, the distance value inquiry at a specific location, real-time raytracing, and collision handling can be performed quickly and efficiently. Using the proposed method, the adaptive sign distance field can be calculated quickly in about 1 second even on a high polygon mesh, so it is a method that can be fully utilized not only for rigid bodies but also for deformable bodies. It shows the stability of the algorithm through various experimental results whether it can accurately sample and represent distance values in various models.
KW - Compute unified device architecture;Adaptive distance field;Data visualization;Collision handling;Rendering
DO - 10.9708/jksci.2022.27.03.063
ER -

Jong-Hyun Kim. (2022). Efficient GPU Framework for Adaptive and Continuous Signed Distance Field Construction, and Its Applications. Journal of The Korea Society of Computer and Information, 27(3), 63-69.

Jong-Hyun Kim. 2022, "Efficient GPU Framework for Adaptive and Continuous Signed Distance Field Construction, and Its Applications", Journal of The Korea Society of Computer and Information, vol.27, no.3 pp.63-69. Available from: doi:10.9708/jksci.2022.27.03.063

Jong-Hyun Kim "Efficient GPU Framework for Adaptive and Continuous Signed Distance Field Construction, and Its Applications" Journal of The Korea Society of Computer and Information 27.3 pp.63-69 (2022) : 63.

Jong-Hyun Kim. Efficient GPU Framework for Adaptive and Continuous Signed Distance Field Construction, and Its Applications. 2022; 27(3), 63-69. Available from: doi:10.9708/jksci.2022.27.03.063

Jong-Hyun Kim. "Efficient GPU Framework for Adaptive and Continuous Signed Distance Field Construction, and Its Applications" Journal of The Korea Society of Computer and Information 27, no.3 (2022) : 63-69.doi: 10.9708/jksci.2022.27.03.063

Jong-Hyun Kim. Efficient GPU Framework for Adaptive and Continuous Signed Distance Field Construction, and Its Applications. Journal of The Korea Society of Computer and Information, 27(3), 63-69. doi: 10.9708/jksci.2022.27.03.063

Jong-Hyun Kim. Efficient GPU Framework for Adaptive and Continuous Signed Distance Field Construction, and Its Applications. Journal of The Korea Society of Computer and Information. 2022; 27(3) 63-69. doi: 10.9708/jksci.2022.27.03.063

Jong-Hyun Kim. Efficient GPU Framework for Adaptive and Continuous Signed Distance Field Construction, and Its Applications. 2022; 27(3), 63-69. Available from: doi:10.9708/jksci.2022.27.03.063

Jong-Hyun Kim. "Efficient GPU Framework for Adaptive and Continuous Signed Distance Field Construction, and Its Applications" Journal of The Korea Society of Computer and Information 27, no.3 (2022) : 63-69.doi: 10.9708/jksci.2022.27.03.063