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A study on garment wrinkle detection through a 3D camera scanning with normal map and Hough transform
Author(s): Makoto Takamatsu; Eizaburo Iwata; Takao Furukawa; Makoto Hasegawa
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Paper Abstract

We discuss material properties of different garment wrinkles. Subjects wear three kinds of different fabric garment: polyester, cotton, and linen. Scanning the subject's 3D body shape using a RGB-D camera and getting a 3DCG model of them. Generating a normal polygonal image applying a baking process. High-poly mesh is generated from low-poly mesh of the 3DCG model, and multiple high polygons are mapped into a low polygon. Computing the normal vectors of the high polygons on the low-poly mesh, generators our normal map image through this process. Garment wrinkles are detected by straight-line recognition on the normal map using Hough transform. Measuring the number of the garment wrinkles, the variation in the direction and position of garment wrinkles, and the length distribution . All properties of the garment wrinkle is necessary for an analysis in our experiment. But it is revealed that the dispersion in the wrinkle direction is important for distinguishing the fabrics.

Paper Details

Date Published: 22 March 2019
PDF: 6 pages
Proc. SPIE 11049, International Workshop on Advanced Image Technology (IWAIT) 2019, 110492U (22 March 2019); doi: 10.1117/12.2521408
Show Author Affiliations
Makoto Takamatsu, Tokyo Denki Univ. (Japan)
Eizaburo Iwata, NORMEE Ltd. (Japan)
Takao Furukawa, Kyoritsu Women's Univ. (Japan)
Makoto Hasegawa, Tokyo Denki Univ. (Japan)


Published in SPIE Proceedings Vol. 11049:
International Workshop on Advanced Image Technology (IWAIT) 2019
Qian Kemao; Kazuya Hayase; Phooi Yee Lau; Wen-Nung Lie; Yung-Lyul Lee; Sanun Srisuk; Lu Yu, Editor(s)

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