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Massively parallel inverse rendering using Multi-objective Particle Swarm Optimization

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Abstract

We present a novel GPU-accelerated per-pixel inverse rendering optimization algorithm based on Particle Swarm Optimization (PSO). Our algorithm estimates the per-pixel scene attributes—including reflectance properties—of a 3D model, and is fast enough to do in situ visualization of the optimization in real-time. The algorithm’s high parallel efficiency is demonstrated through our GPU/GLSL shader implementation of the method. IRPSO is validated experimentally on simulated ground truth images, while a suite of tests performed on the University of Southern California’s High Performance Computing Center cluster provides strong evidence that our method can scale to larger, more difficult inverse rendering problems.

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References

  • Chow CK, Tsui HT (2004) Autonomous agent response learning by a multi-species particle swarm optimization. In: IEEE CEC2004 congress on evolutionary computation, 2004, vol 1, pp 778–785

  • Cook RL, Torrance KE (1982) A reflectance model for computer graphics. ACM TOG 1(1):7–24

    Article  Google Scholar 

  • Debevec PE, Taylor CJ, Malik J (1996) Modeling and rendering architecture from photographs: a hybrid geometry- and image-based approach. In: Proceedings of SIGGRAPH 96, computer graphics proceedings, annual conference series, pp 11–20

  • Donner C, Weyrich T, d’Eon E, Ramamoorthi R, Rusinkiewicz S (2008) A layered, heterogeneous reflectance model for acquiring and rendering human skin. In: ACM TOG (Proceedings of SIGGRAPH Asia)

  • Eberhart R, Kennedy J (1995) A new optimizer using particle swarm theory. In: Proceedings of the sixth international symposium on micro machine and human science, 1995, MHS ’95, pp 39–43. doi:10.1109/MHS.1995.494215

  • Ghosh A, Fyffe G, Tunwattanapong B, Busch J, Yu X, Debevec P (2011) Multiview face capture using polarized spherical gradient illumination. In: Proceedings of the 2011 SIGGRAPH Asia conference, SA ’11. ACM, New York, pp 129:1–129:10. doi:10.1145/2024156.2024163

  • Graham P, Tunwattanapong B, Busch J, Yu X, Jones A, Debevec P, Ghosh A (2013) Measurement-based synthesis of facial microgeometry. Comput Graphics Forum 32(2pt3):335–344. doi:10.1111/cgf.12053

  • Marschner S (1998) Inverse rendering for computer graphics. Ph.D. thesis, Cornell University

  • Nagano K, Collins T, Chen CA, Nakano A (2015) GPU-based inverse rendering with multi-objective particle swarm optimization. In: SIGGRAPH Asia 2015 visualization in high performance computing, SA ’15. ACM, New York, pp 8:1–8:4. doi:10.1145/2818517.2818523

  • Parsopoulos KE, Vrahatis MN (2004) On the computation of all global minimizers through particle swarm optimization. IEEE Trans Evol Comput 8(3):211–224

    Article  Google Scholar 

  • Parsopoulos KE, Vrahatis MN (2008) Multi-objective particles swarm optimization approaches. In: Thu Bui L, Alam S (eds) Multi-objective optimization in computational intelligence: theory and practice. IGI Global, Hershey, pp 20–42

  • Poli R (2008) Analysis of the publications on the applications of particle swarm optimisation. J Artif Evol App 4:1–4:10. doi:10.1155/2008/685175

  • Ramamoorthi R, Hanrahan P (2001) A signal-processing framework for inverse rendering. In: Proceedings of the 28th annual conference on computer graphics and interactive techniques, SIGGRAPH ’01. ACM, New York, pp 117–128. doi:10.1145/383259.383271

  • Sun J, Lai C, Wu X (2011) Particle swarm optimisation: classical and quantum perspectives. Chapman & Hall, London

  • Weyrich T, Matusik W, Pfister H, Bickel B, Donner C, Tu C, McAndless J, Lee J, Ngan A, Jensen HW, Gross M (2006) Analysis of human faces using a measurement-based skin reflectance model. ACM Trans Graph 25(3):1013–1024

    Article  Google Scholar 

  • Yu Y, Debevec P, Malik J, Hawkins T (1999) Inverse global illumination: recovering reflectance models of real scenes from photographs. In: SIGGRAPH ’99, pp 215–224

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Acknowledgments

This work was developed from a final project for CSCI 596 (scientific computing and visualization) course at the University of Southern California. Integration of research and education in CSCI 596 was supported by the National Science Foundation, Grant No. 1508131. We also thank the USC Institute for Creative Technologies for the support of the work.

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  1. University of Southern California, Los Angeles, CA, USA

    Koki Nagano , Thomas Collins, Chi-An Chen & Aiichiro Nakano

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  1. Koki Nagano
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  2. Thomas Collins
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  3. Chi-An Chen
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  4. Aiichiro Nakano
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Correspondence to Koki Nagano .

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Nagano , K., Collins, T., Chen, CA. et al. Massively parallel inverse rendering using Multi-objective Particle Swarm Optimization. J Vis 20, 195–204 (2017). https://doi.org/10.1007/s12650-016-0369-3

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  • DOI: https://doi.org/10.1007/s12650-016-0369-3

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