Light Source Estimation in Synthetic Images

  • Mike Kasper
  • Nima Keivan
  • Gabe Sibley
  • Christoffer Heckman
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9915)

Abstract

We evaluate a novel light source estimation algorithm with synthetic image data generated using a custom path-tracer. We model light as an environment map as light sources at infinity for its benefits in estimation. However the synthetic image data are rendered using spherical area lights as to better represent the physical world as well as challenge our algorithm. In total, we generate 55 random illumination scenarios, consisting of either one or two spherical area lights with different intensities and positioned at different distances from the observed scene. Using this data we are able to tune our optimization parameters and determine under which conditions this algorithm and model representation is best suited.

Keywords

Light source estimation Path-tracing Synthetic data 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Mike Kasper
    • 1
  • Nima Keivan
    • 1
  • Gabe Sibley
    • 1
  • Christoffer Heckman
    • 1
  1. 1.University of ColoradoBoulderUSA

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