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Proceedings Paper

Human detection in depth images via two steps
Author(s): Xi En Cheng; Yi Cheng Li; Jing Fang Hu
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Paper Abstract

Reliable human detection is important for a wide range of applications. In this paper, a particular designed method for real-time human detection has been developed. The method is robustly in cluttered and dynamic environments, and deals with depth images. The method has two steps, first the plausible candidate positions are localized by a super-pixel based segmentation and merging approach. Then we utilize a descriptor encoding the joint of depth difference information and 3D geometric characteristics of human upper body to refine the candidates by a deep randomized decision forest classifier. Our approach, which detects human in depth images, allows very fast speed and high accuracy in three publicly available datasets.

Paper Details

Date Published: 9 August 2018
PDF: 8 pages
Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 108061P (9 August 2018); doi: 10.1117/12.2503112
Show Author Affiliations
Xi En Cheng, Jingdezhen Ceramic Institute (China)
Yi Cheng Li, Jingdezhen Ceramic Institute (China)
Jing Fang Hu, Jingdezhen Ceramic Institute (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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