Estimating Surface Reflectance Properties of a Complex Scene under Captured Natural Illumination

Abstract

We present a process for estimating spatially-varying surface reflectance of a complex scene observed under natural illumination conditions. The process uses a laser-scanned model of the scenes geometry, a set of digital images viewing the scenes surfaces under a variety of natural illumination conditions, and a set of corresponding measurements of the scenes incident illumination in each photograph. The process then employs an iterative inverse global illumination technique to compute surface colors for the scene which, when rendered under the recorded illumination conditions, best reproduce the scenes appearance in the photographs. In our process we measure BRDFs of representative surfaces in the scene to better model the non-Lambertian surface reflectance. Our process uses a novel lighting measurement apparatus to record the full dynamic range of both sunlit and cloudy natural illumination conditions. We employ Monte-Carlo global illumination, multiresolution geometry, and a texture atlas system to perform inverse global illumination on the scene. The result is a lighting-independent model of the scene that can be re-illuminated under any form of lighting. We demonstrate the process on a real-world archaeological site, showing that the technique can produce novel illumination renderings consistent with real photographs as well as reflectance properties that are consistent with ground-truth reflectance measurements.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2004
Accession Number
AD1158491

Entities

People

  • Andrew Gardner
  • Andrew K. Jones
  • Charis Poullis
  • Chris Tchou
  • Jessi Stumpfel
  • Marcos Fajardo
  • Nathaniel Yun
  • Paul Debevec
  • Per Einarsson
  • Philippe Martinez
  • Therese Lundgren
  • Tim Hawkins

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Autonomy
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Cameras
  • Computer Graphics
  • Dynamic Range
  • Geometry
  • Graphics
  • High Dynamic Range
  • High Resolution
  • Image Processing
  • Lasers
  • Light Sources
  • Low Resolution
  • Materials
  • Measurement
  • Optics
  • Photographs
  • Prostheses And Implants
  • Standards
  • Three Dimensional

Readers

  • Computer Vision.
  • Spectroscopy.

Technology Areas

  • Directed Energy