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9 August 2018 Head-heuristic human detection in RGB-D images
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Proceedings Volume 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018); 108061Q (2018) https://doi.org/10.1117/12.2503114
Event: Tenth International Conference on Digital Image Processing (ICDIP 2018), 2018, Shanghai, China
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.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xi En Cheng, Yi Cheng Li, and Yong Kong Peng "Head-heuristic human detection in RGB-D images", Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 108061Q (9 August 2018); https://doi.org/10.1117/12.2503114
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