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Related Experiment Videos

Color from shape from color: a simple formalism with known light sources

Drew1, Brill

  • 1School of Computing Science, Simon Fraser University, Vancouver, British Columbia, Canada. mark@cs.sfu.ca

Journal of the Optical Society of America. A, Optics, Image Science, and Vision
|August 10, 2000
PubMed
Summary

This study introduces a novel color photometric stereo method using a single image to recover surface normals and object colors. The simplified approach enhances stability and accuracy in known lighting environments.

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Area of Science:

  • Computer Vision
  • Computational Imaging
  • Photometry

Background:

  • Photometric stereo traditionally requires multiple images for surface normal recovery.
  • Existing color-based methods often need numerous pixels or are limited to single-colored objects.
  • Prior work by Petrov and Antonova offered a local approach for multicolored objects.

Purpose of the Study:

  • To investigate the application of local color-based methods in a known lighting environment using a single image.
  • To recover both surface normals and object colors simultaneously.
  • To simplify and stabilize existing color photometric stereo techniques.

Main Methods:

  • Utilized a single image under a known, complex lighting environment.
  • Applied a simplified orientation-from-color approach, requiring fewer equations than previous methods.

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  • Employed a robust estimator for patch color estimation where pixel-wise solutions were unstable.
  • Transformed color space to spectrally sharpened sensors for improved accuracy.

    • Main Results:

    • Successfully recovered surface normals and object colors from a single image.
    • Demonstrated increased method stability by reducing required equations.
    • Achieved good accuracy compared to ground truth, especially after color space transformation.
    • Showcased the effectiveness of robust estimation for handling pixel variations.

    Conclusions:

    • A single-image color photometric stereo method is feasible and effective in known lighting.
    • The simplified approach offers improved stability and accuracy.
    • Robust estimation and color space transformation are key to reliable results for multicolored surfaces.