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Enhanced Direct Lighting Using Visibility-Aware Light Sampling

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Abstract
Next event estimation has been widely applied to Monte Carlo rendering methods such as path tracing since estimating direct and indirect lighting separately often enables finding light paths from the eye to the lights effectively. Its success heavily relies on light sampling for direct lighting when a scene contains multiple light sources since each light can contribute differently to the reflected radiance on a surface point. We present a light sampling technique that can guide such a light selection to improve direct lighting. We estimate a spatially-varying function that approximates the contribution of each light on surface points within a discretized local area (i.e., a voxel in an adaptive octree) while considering the visibility between lights and surface points. We then construct a probability distribution function for sampling lights per voxel, which is proportional to our estimated function. We demonstrate that our light sampling technique can significantly improve rendering quality thanks to improved direct lighting with our light sampling.
Author(s)
Noh, GeonuChoi, HajinMoon, Bochang
Issued Date
2023-08-31
Type
Conference Paper
URI
https://scholar.gist.ac.kr/handle/local/21078
Publisher
Computer Graphics Society
Citation
Computer Graphics International 2023
Conference Place
CC
Shanghai, China
Appears in Collections:
Department of AI Convergence > 2. Conference Papers
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