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Color Photometric Stereo Using Multi-Band Camera Constrained by Median Filter and Occluding Boundary.

Journal of imaging·2021
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Example-Based Multispectral Photometric Stereo for Multi-Colored Surfaces.

Daisuke Miyazaki1, Kazuya Uegomori1

  • 1Graduate School of Information Sciences, Hiroshima City University, Hiroshima 731-3194, Japan.

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|April 21, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces an example-based photometric stereo method to accurately estimate surface normals for multicolored objects under colored illumination. This approach overcomes limitations of traditional color photometric stereo, enabling precise surface normal estimation without oversmoothing.

Keywords:
color photometric stereoexample-based photometric stereomultispectral imagingmultispectral lightingphotometric stereo

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Area of Science:

  • Computer Vision
  • Photometry
  • Surface Reconstruction

Background:

  • Traditional photometric stereo requires multiple images under varying light directions.
  • Color photometric stereo uses a single image with multi-colored lights but struggles with multicolored objects.
  • Existing methods often involve complex mathematics, assumptions, and smoothness constraints leading to oversmoothed results.

Purpose of the Study:

  • To develop an example-based photometric stereo method for accurate surface normal estimation of multicolored objects.
  • To overcome the limitations of conventional color photometric stereo, particularly its inability to handle multicolored objects under colored illumination.
  • To provide a pixelwise surface normal estimation technique free from mathematical complexities and oversmoothing.

Main Methods:

  • An example-based photometric stereo approach is utilized, referencing a database of known shapes.
  • Surface normals are searched from this database on a pixel-by-pixel basis.
  • A multispectral photometric stereo device with sixteen colors was employed for validation, surpassing the typical three-color systems.

Main Results:

  • The proposed example-based method successfully estimates surface normals for multicolored objects, a challenge for conventional color photometric stereo.
  • The pixelwise processing avoids the oversmoothing issues associated with smoothness constraints in other methods.
  • Validation using a sixteen-color multispectral system demonstrates the robustness and effectiveness of the approach.

Conclusions:

  • Example-based photometric stereo offers a robust solution for surface normal estimation of multicolored objects under complex lighting.
  • This method circumvents the mathematical difficulties and oversmoothing inherent in traditional photometric stereo techniques.
  • The pixelwise, example-based approach provides accurate and detailed surface normal maps.