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ABSTRACT

Graphics hardware is undergoing a change from fixed-function pipelines to more programmable organizations that resemble general purpose stream processors. In this paper, we show that certain general algorithms, not normally associated with computer graphics, can be mapped to such designs. Specifically, we cast nonlinear optimization as a data streaming process that is well matched to modern graphics processors. Our framework is particularly well suited for solving image-based modeling problems since it can be used to represent a large and diverse class of these problems using a common formulation. We successfully apply this approach to two distinct image-based modeling problems: light field mapping approximation and fitting the Lafortune model to spatial bidirectional reflectance distribution functions. Comparing the performance of the graphics hardware implementation to a CPU implementation, we show more than 5-fold improvement.

REFERENCES

• 1: Christopher M. Bishop, Neural Networks for Pattern Recognition, Oxford University Press, Inc., New York, NY, 1995
• 2: Jeff Bolz , Ian Farmer , Eitan Grinspun , Peter Schröoder, Sparse matrix solvers on the GPU: conjugate gradients and multigrid, ACM Transactions on Graphics (TOG), v.22 n.3, July 2003
• 3: CARR, N. A., HALL, J. D., AND HART, J. C. 2002. Ray Engine. 2000 SIGGRAPH / Eurographics Workshop on Graphics Hardware, 1--10.
• 4: Wei-Chao Chen , Jean-Yves Bouguet , Michael H. Chu , Radek Grzeszczuk, Light field mapping: efficient representation and hardware rendering of surface light fields, ACM Transactions on Graphics (TOG), v.21 n.3, July 2002
• 5: J. E. Dennis, Jr. , Robert B. Schnabel, Numerical Methods for Unconstrained Optimization and Nonlinear Equations (Classics in Applied Mathematics, 16), Soc for Industrial & Applied Math, 1996
• 6: R. Furukawa , H. Kawasaki , K. Ikeuchi , M. Sakauchi, Appearance based object modeling using texture database: acquisition, compression and rendering, Proceedings of the 13th Eurographics workshop on Rendering, June 26-28, 2002, Pisa, Italy
• 7: Mark J. Harris , Greg Coombe , Thorsten Scheuermann , Anselmo Lastra, Physically-based visual simulation on graphics hardware, Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware, September 01-02, 2002, Saarbrucken, Germany
• 8: Kenneth E. Hoff, III , John Keyser , Ming Lin , Dinesh Manocha , Tim Culver, Fast computation of generalized Voronoi diagrams using graphics hardware, Proceedings of the 26th annual conference on Computer graphics and interactive techniques, p.277-286, July 1999 [doi>10.1145/311535.311567]
• 9: KAUTZ, J., AND MCCOOL, M. D. 1999. Interactive Rendering with Arbitrary BRDFs using Separable Approximations. Eurographics Rendering Workshop 1999 (June).
• 10: Brucek Khailany , William J. Dally , Ujval J. Kapasi , Peter Mattson , Jinyung Namkoong , John D. Owens , Brian Towles , Andrew Chang , Scott Rixner, Imagine: Media Processing with Streams, IEEE Micro, v.21 n.2, p.35-46, March 2001 [doi>10.1109/40.918001]
• 11: Jens Krüger , Rüdiger Westermann, Linear algebra operators for GPU implementation of numerical algorithms, ACM Transactions on Graphics (TOG), v.22 n.3, July 2003
• 12: Eric P. F. Lafortune , Sing-Choong Foo , Kenneth E. Torrance , Donald P. Greenberg, Non-linear approximation of reflectance functions, Proceedings of the 24th annual conference on Computer graphics and interactive techniques, p.117-126, August 1997 [doi>10.1145/258734.258801]
• 13: Erik Lindholm , Mark J. Kligard , Henry Moreton, A user-programmable vertex engine, Proceedings of the 28th annual conference on Computer graphics and interactive techniques, p.149-158, August 2001 [doi>10.1145/383259.383274]
• 14: David K. McAllister , Anselmo Lastra , Wolfgang Heidrich, Efficient rendering of spatial bi-directional reflectance distribution functions, Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware, September 01-02, 2002, Saarbrucken, Germany
• 15: Michael D. McCool , Jason Ang , Anis Ahmad, Homomorphic factorization of BRDFs for high-performance rendering, Proceedings of the 28th annual conference on Computer graphics and interactive techniques, p.171-178, August 2001 [doi>10.1145/383259.383276]
• 16: NISHINO, K., SATO, Y., AND IKEUCHI, K. 1999. Eigen-Texture Method: Appearance Compression Based on 3D Model. In Proceedings of the IEEE Computer Science Conference on Computer Vision and Pattern Recognition (CVPR-99), 618--624.
• 17: Timothy J. Purcell , Ian Buck , William R. Mark , Pat Hanrahan, Ray tracing on programmable graphics hardware, ACM Transactions on Graphics (TOG), v.21 n.3, July 2002
• 18: Yoichi Sato , Mark D. Wheeler , Katsushi Ikeuchi, Object shape and reflectance modeling from observation, Proceedings of the 24th annual conference on Computer graphics and interactive techniques, p.379-387, August 1997 [doi>10.1145/258734.258885]
• 19: STRZODKA, R., AND RUMPF, M. 2001. Nonlinear Diffusion in Graphics Hardware. Proceedings EG/IEEE TCVG Symposium on Visualization, 75--84.
• 20: Chris J. Thompson , Sahngyun Hahn , Mark Oskin, Using modern graphics architectures for general-purpose computing: a framework and analysis, Proceedings of the 35th annual ACM/IEEE international symposium on Microarchitecture, November 18-22, 2002, Istanbul, Turkey
• 21: Ruigang Yang , Greg Welch , Gary Bishop, Real-Time Consensus-Based Scene Reconstruction Using Commodity Graphics Hardware, Proceedings of the 10th Pacific Conference on Computer Graphics and Applications, p.225, October 09-11, 2002
• 22: Yizhou Yu , Paul Debevec , Jitendra Malik , Tim Hawkins, Inverse global illumination: recovering reflectance models of real scenes from photographs, Proceedings of the 26th annual conference on Computer graphics and interactive techniques, p.215-224, July 1999 [doi>10.1145/311535.311559]

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.3 COMPUTER GRAPHICS
      I.3.1 Hardware architecture
          Subjects: Graphics processors

Additional Classification:
  I. Computing Methodologies
  I.3 COMPUTER GRAPHICS
      I.3.3 Picture/Image Generation
          Subjects: Viewing algorithms; Digitizing and scanning

Keywords:
image-based modeling, nonlinear optimization, programmable graphics hardware