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Mesostructure from Specularity
New York, NY June 17-June 22
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CVPR.2006.1822006 IEEE Computer Society Conference ...
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Tongbo Chen, MPI Informatik
Michael Goesele, University of Washington
Hans-Peter Seidel, MPI Informatik
We describe a simple and robust method for surface mesostructure acquisition. Our method builds on the observation that specular reflection is a reliable visual cue for surface mesostructure perception. In contrast to most photometric stereo methods, which take specularities as outliers and discard them, we propose a progressive acquisition system that captures a dense specularity field as the only information for mesostructure reconstruction. Our method can efficiently recover surfaces with fine-scale geometric details from complex real-world objects with a wide variety of reflection properties, including translucent, low albedo, and highly specular objects. We show results for a variety of objects including human skin, dried apricot, orange, jelly candy, black leather and dark chocolate.
Citation:
Tongbo Chen, Michael Goesele, Hans-Peter Seidel, "Mesostructure from Specularity," cvpr, vol. 2, pp.1825-1832, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (CVPR'06), 2006
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