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.
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Inoshita, C., Mukaigawa, Y., Matsushita, Y., Yagi, Y. (2014). Surface Normal Deconvolution: Photometric Stereo for Optically Thick Translucent Objects. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds) Computer Vision – ECCV 2014. ECCV 2014. Lecture Notes in Computer Science, vol 8690. Springer, Cham. https://doi.org/10.1007/978-3-319-10605-2_23
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DOI: https://doi.org/10.1007/978-3-319-10605-2_23
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