State of the Art in Photon Density Estimation

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Abstract

Photon density estimation techniques are a popular choice for simulating light transport in scenes with complicated geometry and materials. This class of algorithms can be used to accurately simulate inter-reflections, caustics, color bleeding, scattering in participating media, and subsurface scattering. Since its introduction, photon density estimation has been significantly extended in computer graphics with the introduction of: specialized techniques that intelligently modify the positions or bandwidths to reduce visual error using a small number of photons, approaches which eliminate error completely in the limit, methods that use higher-order samples and queries to reduce error in participating media, and recent generalized formulations that bridge the gap between photon density estimation and other techniques. This course provides the necessary insight to implement all these latest advances in photon density estimation. The course starts out with a short introduction to photon density estimation using classical photon mapping, but the remainder of the two-part course provides hands-on explanations of the latest developments in this area by the experts behind each technique. The course will give the audience concrete and practical understanding of the latest developments in photon density estimation techniques that have not been presented in prior similar SIGGRAPH/SIGGRAPH Asia courses.

Syllabus & Schedule

9:00	Introduction (Jarosz) slides
	Regular Photon Density Estimation
9:05	Photon Mapping Basics (Jarosz) slides
	Progressive Photon Density Estimation
9:23	Progressive Photon Mapping - Basics (Hachisuka) slides
9:38	Probabilistic PPM (Hachisuka) slides
9:53	Progressive Photon Mapping - Extensions (Hachisuka) slides
10:16	Adaptive PPM (Kaplanyan) slides & notes | slides & notes
	Participating Media
10:34	Participating Media Basics (Jarosz) slides
10:49	From Photons to Beams (Jarosz) slides
11:12	Photon Beams in Tangled (Nowrouzezahrai) slides
	Beyond Density Estimation
11:30	Photon Relaxation and Extensions (Hachisuka) slides
11:48	Progressive EM (Jarosz) slides
12:01	Unified Formulation and Regularization (Georgiev and Kaplanyan) slides & notes (Georgiev) | slides & notes (Georgiev) | slides & notes (Kaplanyan) | slides & notes (Kaplanyan)
12:34	Conclusions (Hachisuka) slides