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Erschienen in:
2014 | OriginalPaper | Buchkapitel
Surface Normal Deconvolution: Photometric Stereo for Optically Thick Translucent Objects
verfasst von : Chika Inoshita, Yasuhiro Mukaigawa, Yasuyuki Matsushita, Yasushi Yagi
Erschienen in: Computer Vision – ECCV 2014
Verlag: Springer International Publishing
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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.