Enhanced Photometric Stereo with Multispectral Images

We introduce a technique based on multispectral images aimed at improving Lambertian photometric stereo. Many photometric stereo algorithms assume Lambertian reflectance, but deviations from this ideal produce errors in shape reconstruction. To alleviate this problem, we exploit the wavelength-dependence of material reflectance. Based on the observation that reflectance at certain wavelengths for a given object is more Lambertian than at others, we propose a method for identifying such wavelengths by a matrix rank analysis, and use them to achieve more accurate photometric stereo. We merge reconstruction results from different wavelengths to produce the final surface normal map. Experimental results on synthetic and real data demonstrate the greater accuracy of this method compared to conventional photometric stereo based on brightness images.

Authors

  • Tsuyoshi Takatani
  • Yasuyuki Matsushita
  • Stephen Lin
  • Yasuhiro Mukaigawa
  • Yasushi Yagi

Documents

Citation


@inproceedings{takatani2013enhanced,
title={Enhanced Photometric Stereo with Multispectral Images.},
author={Takatani, Tsuyoshi and Matsushita, Yasuyuki and Lin, Stephen and Mukaigawa, Yasuhiro and Yagi, Yasushi},
booktitle={Proc. of IAPR International Conference on Machine Vision Applications (MVA)},
pages={343–346},
month={May},
year={2013}
}

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