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Homomorphic factorization of BRDFs for high-performance rendering
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Source International Conference on Computer Graphics and Interactive Techniques archive
Proceedings of the 28th annual conference on Computer graphics and interactive techniques table of contents
Pages: 171 - 178  
Year of Publication: 2001
ISBN:1-58113-374-X
Authors
Michael D. McCool  Computer Graphics Lab., Department of Computer Science, University of Waterloo
Jason Ang  Computer Graphics Lab., Department of Computer Science, University of Waterloo
Anis Ahmad  Computer Graphics Lab., Department of Computer Science, University of Waterloo
Sponsor
SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 13,   Downloads (12 Months): 90,   Citation Count: 30
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ABSTRACT

A bidirectional reflectance distribution function (BRDF) describes how a material reflects light from its surface. To use arbitrary BRDFs in real-time rendering, a compression technique must be used to represent BRDFs using the available texture-mapping and computational capabilities of an accelerated graphics pipeline. We present a numerical technique, homomorphic factorization, that can decompose arbitrary BRDFs into products of two or more factors of lower dimensionality, each factor dependent on a different interpolated geometric parameter. Compared to an earlier factorization technique based on the singular value decomposition, this new technique generates a factorization with only positive factors (which makes it more suitable for current graphics hardware accelerators), provides control over the smoothness of the result, minimizes relative rather than absolute error, and can deal with scattered, sparse data without a separate resampling and interpolation algorithm.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  31

Collaborative Colleagues:
Michael D. McCool: colleagues
Jason Ang: colleagues
Anis Ahmad: colleagues