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Surface Normal Deconvolution: Photometric Stereo for Optically Thick Translucent Objects

  • Chika Inoshita
  • Yasuhiro Mukaigawa
  • Yasuyuki Matsushita
  • Yasushi Yagi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8690)

Abstract

This paper presents a photometric stereo method that works for optically thick translucent objects exhibiting subsurface scattering. Our method is built upon the previous studies showing that subsurface scattering is approximated as convolution with a blurring kernel. We extend this observation and show that the original surface normal convolved with the scattering kernel corresponds to the blurred surface normal that can be obtained by a conventional photometric stereo technique. Based on this observation, we cast the photometric stereo problem for optically thick translucent objects as a deconvolution problem, and develop a method to recover accurate surface normals. Experimental results of both synthetic and real-world scenes show the effectiveness of the proposed method.

Keywords

Convolution Kernel Blind Deconvolution Photometric Stereo Translucent Material Subsurface Scattering 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Chika Inoshita
    • 1
  • Yasuhiro Mukaigawa
    • 2
  • Yasuyuki Matsushita
    • 3
  • Yasushi Yagi
    • 1
  1. 1.Osaka UniversityJapan
  2. 2.Nara Institute of Science and TechnologyJapan
  3. 3.Microsoft Research AsiaChina

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