arrow
Return

Photon mapping with visible kernel domains

delete2018-04-06
delete0
PRE
AI
R
Romuald Perrot
L
Lilian Aveneau
F
Frédéric Mora
D
Daniel Méneveaux *
DOI:10.1007/s00371-018-1505-ydelete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Despite the strong efforts made in the last three decades, lighting simulation systems still remain prone to various types of imprecisions. This paper specifically tackles the problem of biases due to density estimation used in photon mapping approaches. We study the fundamental aspects of density estimation and exhibit the need for handling visibility in the early stage of the kernel domain definition. We show that properly managing visibility in the density estimation process allows to reduce or to remove biases all at once. In practice, we have implemented a 3D product kernel based on a polyhedral domain, with both point-to-point and point-to-surface visibility computation. Our experimental results illustrate the enhancements produced at every stage of density estimation, for direct photon maps visualization and progressive photon mapping.
Keywords:
Lighting simulation
Photon mapping
Density estimation
Visibility
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Visual Computer cover
Visual Computer
IF:
2.9
Papers:
4.6K
Citations:
6.5K

Organization

U
universite de poitiers
Scholars:
7.1K
Papers: 5.0K
Citations: 5
U
universite de limoges
Scholars:
3.1K
Papers: 2.1K
Citations: 2