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Head-heuristic human detection in RGB-D images
Author(s): Xi En Cheng; Yi Cheng Li; Yong Kong Peng
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Paper Abstract

Reliable human detection and tracking is important for a wide range of applications. In this paper, a particular designed method for real-time human detection has been proposed. The method is robustly in cluttered and dynamic environments, and deals with depth images. The method has two steps, first the hypothesis human head regions are localized by a superpixel based segmentation and merging approach. Then we utilize a multi-channel measurement and employ neural network for classification between human and non-human region refinement. 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), 108061Q (9 August 2018); doi: 10.1117/12.2503114
Show Author Affiliations
Xi En Cheng, Jingdezhen Ceramic Institute (China)
Yi Cheng Li, Jingdezhen Ceramic Institute (China)
Yong Kong Peng, 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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