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Related Experiment Video

Updated: Jun 8, 2026

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
05:12

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery

Published on: August 12, 2021

Overcoming shadows in 3-source photometric stereo.

Carlos Hernández1, George Vogiatzis, Roberto Cipolla

  • 1Google Inc., Seattle, WA 98103, USA. carloshernandez@google.com

IEEE Transactions on Pattern Analysis and Machine Intelligence
|October 6, 2010
PubMed
Summary
This summary is machine-generated.

This study addresses light occlusions in photometric stereo, especially with limited two-image data. Regularization methods are introduced to resolve ambiguity and reconstruct geometry in shadowed areas, improving shape recovery.

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Measuring Spatially- and Directionally-varying Light Scattering from Biological Material
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Measuring Spatially- and Directionally-varying Light Scattering from Biological Material

Published on: May 20, 2013

Related Experiment Videos

Last Updated: Jun 8, 2026

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
05:12

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery

Published on: August 12, 2021

Measuring Spatially- and Directionally-varying Light Scattering from Biological Material
11:57

Measuring Spatially- and Directionally-varying Light Scattering from Biological Material

Published on: May 20, 2013

Area of Science:

  • Computer Vision
  • Photometric Stereo
  • Surface Reconstruction

Background:

  • Light occlusions pose significant challenges in photometric stereo.
  • Overdetermined systems (3+ images) allow discarding shadowed pixels, but two-image scenarios present ambiguities.

Purpose of the Study:

  • To investigate and resolve the one-degree-of-freedom ambiguity per pixel in photometric stereo with only two images.
  • To develop regularization schemes for accurate geometry reconstruction in shadowed regions.

Main Methods:

  • Analysis of integrability for resolving orientation ambiguity.
  • Development and application of two regularization schemes to improve numerical performance.
  • Extension of the theory to color photometric stereo with limited images.

Main Results:

  • Integrability alone is insufficient to resolve ambiguity in noisy two-image photometric stereo.
  • Regularization schemes enhance algorithm performance and preserve data integrity.
  • The proposed methods are validated through experiments on synthetic and real image data.

Conclusions:

  • The developed regularization techniques effectively address the challenges of light occlusions in two-image photometric stereo.
  • The approach is applicable to color photometric stereo, improving reconstruction accuracy under common occlusion conditions.