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Conference Paper

Progressive Path Tracing with Lightweight Local Error Estimation

MPS-Authors

Dmitriev,  Kirill
Max Planck Society;

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Seidel,  Hans-Peter       
Computer Graphics, MPI for Informatics, Max Planck Society;

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Citation

Dmitriev, K., & Seidel, H.-P. (2004). Progressive Path Tracing with Lightweight Local Error Estimation. In B. Girod, M. A. Magnor, & H.-P. Seidel (Eds.), Vision, modeling, and visualization 2004 (pp. 249-254). Berlin, Germany: Akademische Verlagsgesellschaft Aka.


Cite as: https://hdl.handle.net/11858/00-001M-0000-000F-2B05-C
Abstract
Adaptive sampling techniques typically applied in path tracing are not
progressive. The reason is that they need all the samples used to compute
pixel color for error estimation. Thus progressive computation would need
to store all the samples for all the pixels, which is too expensive.
Absence of progressivity is a big disadvantage of adaptive path tracing
algorithms because a user may become aware of some unwanted effects on the
image only after quite significant time. We propose a new estimate of local
error in path tracing. The new technique happens to be lightweight in terms
of both memory and execution time and lends itself very well to
progressivity. Also, even thought perceptual error metric is used, it
allows changes of any tone mapping parameters during the course of
computation. In this case none of the previous effort is lost, error
distribution is immediately updated and used for refining the solution.