Computer Graphics, 26, 2, July 1992 * An Importance-Driven Radiosity Algorithm Brian E. Smits James R. Ar\w Da~ id H. Sulesin Program of Computer Graphics Cornell University Ithaca, NY 14853 Abstract We present a new radiosi[y algorithm for efficiently computing global solutions with respect to a constrained set of views. Radiosi ties of directly visible surfaces are computed to high accuracy, while those ot surfaces having only an indirect effect are computed to an accuracy commensurate with their contribution. The algorithm uses an adaptive subdivision scheme that is guided by the interplay between two closely related transport processes: one propagating power from the light sources, and the other propagating imporrarwc from the visible surfaces. By simultaneously refining approximate solutions to the dud transport equations, computation is significantly reduced in areas that contribute little to the region of interest. This approach is very effective for complex environments in which only a small fraction is visible at any time. Our statistics show dramatic speedups over the fastest previous radiosity algorithms for diffuse environments with details at a wide range of scales. cant intensity gradients occur [3. 4. 6]. These algorithms can achieve good results with fewer surface elements. For
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An importance-driven radiosity algorithm
Smits, Brian E.; Arvo, James R.; Salesin, David H.
Follow ACM SIGGRAPH Computer Graphics
, Volume 26 (2)
Association for Computing Machinery – Jul 1, 1992
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