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Fast computation of shadow boundaries using spatial coherence and backprojections

Published:24 July 1994Publication History

ABSTRACT

This paper describes a fast, practical algorithm to compute the shadow boundaries in a polyhedral scene illuminated by a polygonal light source. The shadow boundaries divide the faces of the scene into regions such that the structure or “aspect” of the visible area of the light source is constant within each region. The paper also describes a fast, practical algorithm to compute the structure of the visible light source in each region. Both algorithms exploit spatial coherence and are the most efficient yet developed.

Given the structure of the visible light source in a region, queries of the form “What specific areas of the light source are visible?” can be answered almost instantly from any point in the region. This speeds up by several orders of magnitude the accurate computation of first level diffuse reflections due to an area light source. Furthermore, the shadow boundaries form a good initial decomposition of the scene for global illumination computations.

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References

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      cover image ACM Conferences
      SIGGRAPH '94: Proceedings of the 21st annual conference on Computer graphics and interactive techniques
      July 1994
      512 pages
      ISBN:0897916670
      DOI:10.1145/192161

      Copyright © 1994 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: 24 July 1994

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      SIGGRAPH '94 Paper Acceptance Rate57of242submissions,24%Overall Acceptance Rate1,822of8,601submissions,21%

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