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9 August 2018 Human detection in depth images via two steps
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Proceedings Volume 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018); 108061P (2018) https://doi.org/10.1117/12.2503112
Event: Tenth International Conference on Digital Image Processing (ICDIP 2018), 2018, Shanghai, China
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.
© (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 Jing Fang Hu "Human detection in depth images via two steps", Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 108061P (9 August 2018); https://doi.org/10.1117/12.2503112
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