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Proceedings Paper

Automatic segmentation of human depth map based on semantic segmentation of FCN and depth segmentation
Author(s): Ruifeng Yuan; Mei Hui; Ming Liu; Yuejin Zhao; Liquan Dong; Lingqin Kong; Ming Chang; Zhi Cai
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Paper Abstract

Traditional 3D information acquisition of human body relies on either foreground extraction or threshold segmentation in a plain background. It is difficult to be applied directly in complex background. In this paper, a novel method is proposed on the basis of binocular vision, which combines the semantic segmentation of FCN with the depth segmentation to get the human body depth map. The depth map is obtained by binocular camera, and each point in the depth map corresponds to the point in the left camera image. The position of the human body is gained through semantic segmentation of the left camera image, then automatic depth segmentation can be conducted based on the depth of human body in the depth map. The final result is obtained by taking the intersection of the depth map segmentation result and the left camera image segmentation result. The results show that the segmentation precision is much higher than that of purely semantic segmentation of FCN, the segmentation accuracy has increased about 2%.

Paper Details

Date Published: 9 August 2018
PDF: 8 pages
Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 108062R (9 August 2018); doi: 10.1117/12.2502880
Show Author Affiliations
Ruifeng Yuan, Beijing Institute of Technology (China)
Mei Hui, Beijing Institute of Technology (China)
Ming Liu, Beijing Institute of Technology (China)
Yuejin Zhao, Beijing Institute of Technology (China)
Liquan Dong, Beijing Institute of Technology (China)
Lingqin Kong, Beijing Institute of Technology (China)
Ming Chang, Beijing Institute of Technology (China)
Zhi Cai, Beijing Institute of Technology (China)


Published in SPIE Proceedings Vol. 10806:
Tenth International Conference on Digital Image Processing (ICDIP 2018)
Xudong Jiang; Jenq-Neng Hwang, Editor(s)

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