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Real-time volume caustics with adaptive beam tracing

Published:18 February 2011Publication History

ABSTRACT

Caustics are detailed patterns of light reflected or refracted on specular surfaces into participating media or onto surfaces. In this paper we present a novel adaptive and scalable algorithm for rendering surface and volume caustics in single-scattering participating media at real-time frame rates. Motivated by both caustic mapping and triangle-based volumetric methods, our technique captures the specular surfaces in light-space, but traces beams of light instead of single photons. The beams are adaptively generated from a grid projected from the light source onto the scene's surfaces, which is iteratively refined according to discontinuities in the geometry and photon distribution. This allows us to reconstruct sharp volume caustic patterns while reducing sampling resolution and fill-rate at defocused regions. We demonstrate our technique combined with approximate ray tracing techniques to render surfaces with two-sided refractions as well as multiple caustic light bounces.

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References

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      • Published in

        cover image ACM Conferences
        I3D '11: Symposium on Interactive 3D Graphics and Games
        February 2011
        207 pages
        ISBN:9781450305655
        DOI:10.1145/1944745

        Copyright © 2011 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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        Publication History

        • Published: 18 February 2011

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        I3D '11 Paper Acceptance Rate24of64submissions,38%Overall Acceptance Rate148of485submissions,31%

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