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ABSTRACT
We describe a system that computes radiosity solutions for polygonal environments much larger than can be stored in main memory. The solution is stored in and retrieved from a database as the computation proceeds. Our system is based on two ideas: the use of visibility oracles to find source and blocker surfaces potentially visible to a receiving surface; and the use of hierarchical techniques to represent interactions between large surfaces efficiently, and to represent the computed radiosity solution compactly. Visibility information allows the environment to be partitioned into subsets, each containing all the information necessary to transfer light to a cluster of receiving polygons. Since the largest subset needed for any particular cluster is much smaller than the total size of the environment, these subset computations can be performed in much less memory than can classical or hierarchical radiosity. The computation is then ordered for further efficiency. Careful ordering of energy transfers minimizes the number of database reads and writes. We report results from large solutions of unfurnished and furnished buildings, and show that our implementation's observed running time scales nearly linearly with both local and global model complexity.
REFERENCES
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CITED BY 19
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Luc Renambot , Bruno Arnaldi , Thierry Priol , Xavier Pueyo, Towards efficient parallel radiosity for DSM-based parallel computers using virtual interfaces, Proceedings of the IEEE symposium on Parallel rendering, p.79-86, October 20-21, 1997, Phoenix, Arizona, United States
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Daniel Meneveaux , Kadi Bouatouch , Gilles Subrenat , Philippe Blasi, Efficient clustering and visibility calculation for global illumination, Proceedings of the 2nd international conference on Computer graphics, virtual Reality, visualisation and interaction in Africa, February 03-05, 2003, Cape Town, South Africa
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David Johnson , Shankar Krishnan , Jatin Chhugani , Subodh Kumar , Suresh Venkatasubramanian, Compressing large boolean matrices using reordering techniques, Proceedings of the Thirtieth international conference on Very large data bases, p.13-23, August 31-September 03, 2004, Toronto, Canada
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David Zareski , Bretton Wade , Philip Hubbard , Peter Shirley, Efficient parallel global illumination using density estimation, Proceedings of the IEEE symposium on Parallel rendering, p.47-54, October 30-31, 1995, Atlanta, Georgia, United States
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