Paper Info
Title
Grouped photon mapping
Abstract
This paper proposes a novel architecture called Grouped Photon Mapping, which combines standard photon mapping with the light-beam concept to improve the nearest-neighbor density estimation method. Based on spatial coherence, we cluster all of photons, which are deposited in the photon map, into different beam-like groups. Each group of photons is individually stored in an isolated photon map. By the distribution of the photons in each photon map, we construct a polygonal boundary to represent a beam-like illuminated area. These boundaries offer a more accurate and flexible sampling area to filter neighbor photons around the query point. In addition, by a level of detail technique, we can control the photon-count in each group to obtain a balance between biases and noise. The results of our experiments prove that our method can successfully reduce bias errors and light leakage. Especially, for complicated caustic effects through a gemstone-like object, we can render a smoother result than standard photon mapping.
Year
DOI
Venue
2010
10.1007/s00371-009-0397-2
The Visual Computer
Keywords
Field
DocType
nearest-neighbor density estimation method,beam-like illuminated area,isolated photon map,different beam-like group,standard photon mapping,photon mapping,neighbor photon,photon mapping · density estimation · global illumination · caustics,photon map,grouped photon mapping,bias error,flexible sampling area,global illumination,caustics,level of detail,density estimation,nearest neighbor
Density estimation,Computer vision,Photon,Polygon,Computer science,Caustic (optics),Level of detail,Artificial intelligence,Global illumination,Photon mapping,Monte Carlo method for photon transport
Journal
Volume
Issue
ISSN
26
3
1432-2315
Citations 
PageRank 
References 
3
0.41
7
Authors
3
Name
Order
Citations
PageRank
Lieu-Hen Chen1539.93
Tsung-Chih Tsai240.77
Yu-Sheng Chen3638.02