Metropolis photon sampling with optional user guidance

  • Authors:
  • Shaohua Fan;Stephen Chenney;Yu-chi Lai

  • Affiliations:
  • University of Wisconsin, Madison;University of Wisconsin, Madison;University of Wisconsin, Madison

  • Venue:
  • EGSR'05 Proceedings of the Sixteenth Eurographics conference on Rendering Techniques
  • Year:
  • 2005

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Abstract

We present Metropolis Photon Sampling (MPS), a visual importance-driven algorithm for populating photon maps. Photon Mapping and other particle tracing algorithms fail if the photons are poorly distributed. Our approach samples light transport paths that join a light to the eye, which accounts for the viewer in the sampling process and provides information to improve photon storage. Paths are sampled with a Metropolis-Hastings algorithm that exploits coherence among important light paths. We also present a technique for including user selected paths in the sampling process without introducing bias. This allows a user to provide hints about important paths or reduce variance in specific parts of the image. We demonstrate MPS with a range of scenes and show quantitative improvements in error over standard Photon Mapping and Metropolis Light Transport.