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Subpixel photometric stereo.

Ping Tan1, Stephen Lin, Long Quan

  • 1Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Kowlon, Hong Kong. ptan@cse.ust.hk

IEEE Transactions on Pattern Analysis and Machine Intelligence
|June 21, 2008
PubMed
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This study introduces a new photometric stereo method to recover subpixel surface geometry. The approach enhances geometric resolution beyond input image limits by analyzing reflectance properties and surface normals.

Area of Science:

  • Computer Vision
  • Computer Graphics
  • Computational Imaging

Background:

  • Conventional photometric stereo is limited to pixel-level geometric recovery.
  • Subpixel geometric structures cannot be modeled with existing methods.
  • Existing techniques lack the resolution for fine geometric details.

Purpose of the Study:

  • To develop a method for recovering subpixel surface geometry.
  • To overcome the resolution limitations of conventional photometric stereo.
  • To enable the modeling of finer geometric details on surfaces.

Main Methods:

  • A generalized physically-based reflectance model was developed.
  • The distribution of surface normals and subpixel convexity were computed from reflectance functions.

Related Experiment Videos

  • Belief propagation and Markov Chain Monte Carlo (MCMC) were used for optimization.

    • Main Results:

    • The method successfully recovers subpixel surface geometry.
    • Enhanced geometric resolution beyond the input image resolution was achieved.
    • The approach demonstrates superior geometric resolution compared to conventional methods.

    Conclusions:

    • The proposed photometric stereo method effectively recovers subpixel surface geometry.
    • This technique significantly improves the geometric resolution of recovered surfaces.
    • The findings enable more detailed 3D surface reconstruction.