Human detection in depth images via two steps

Xi En Cheng; Yi Cheng Li; Jing Fang Hu

doi:10.1117/12.2503112

9 August 2018 Human detection in depth images via two steps

Xi En Cheng, Yi Cheng Li, Jing Fang Hu

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.

Citation Download Citation

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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