@article{ART003280480},
author={Jong-Hyun Kim},
title={Efficient Ambient Occlusion Computation in Point Clouds},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2025},
volume={30},
number={12},
pages={167-175}
TY - JOUR
AU - Jong-Hyun Kim
TI - Efficient Ambient Occlusion Computation in Point Clouds
JO - Journal of The Korea Society of Computer and Information
PY - 2025
VL - 30
IS - 12
PB - The Korean Society Of Computer And Information
SP - 167
EP - 175
SN - 1598-849X
AB - Ambient Occlusion (AO) is a core technique that enhances depth perception and shape recognition by darkening regions where ambient light is less likely to reach, such as creases and cavities. However, screen-space ambient occlusion (SSAO) assumes mesh connectivity, making it difficult to apply directly to point-set data lacking explicit surface structure. This study proposes an efficient AO computation framework for point sets by combining normal estimation, spherical neighborhood search, planar position evaluation, and normal–directional angle weighting, with min–max normalization and an adjustable intensity parameter to control shading. The system is implemented in Unity3D, representing points as small spherical objects and evaluating local geometric relationships through dot-product and angular calculations to assign AO intensity. Experiments on various point models demonstrate consistent and stable shading effects under different intensity levels. In summary, the proposed method enables accurate and coherent AO visualization without mesh connectivity, offering practical benefits for real-time visualization, scanned-data rendering, and game/VR applications.
KW - Point Set;Ambient Occlusion;Normal Vector Estimation;Real-Time Visualization;;Unity3D Framework
DO -
UR -
ER -
Jong-Hyun Kim. (2025). Efficient Ambient Occlusion Computation in Point Clouds. Journal of The Korea Society of Computer and Information, 30(12), 167-175.
Jong-Hyun Kim. 2025, "Efficient Ambient Occlusion Computation in Point Clouds", Journal of The Korea Society of Computer and Information, vol.30, no.12 pp.167-175.
Jong-Hyun Kim "Efficient Ambient Occlusion Computation in Point Clouds" Journal of The Korea Society of Computer and Information 30.12 pp.167-175 (2025) : 167.
Jong-Hyun Kim. Efficient Ambient Occlusion Computation in Point Clouds. 2025; 30(12), 167-175.
Jong-Hyun Kim. "Efficient Ambient Occlusion Computation in Point Clouds" Journal of The Korea Society of Computer and Information 30, no.12 (2025) : 167-175.
Jong-Hyun Kim. Efficient Ambient Occlusion Computation in Point Clouds. Journal of The Korea Society of Computer and Information, 30(12), 167-175.
Jong-Hyun Kim. Efficient Ambient Occlusion Computation in Point Clouds. Journal of The Korea Society of Computer and Information. 2025; 30(12) 167-175.
Jong-Hyun Kim. Efficient Ambient Occlusion Computation in Point Clouds. 2025; 30(12), 167-175.
Jong-Hyun Kim. "Efficient Ambient Occlusion Computation in Point Clouds" Journal of The Korea Society of Computer and Information 30, no.12 (2025) : 167-175.
