Using YOLO-based pedestrian detection for monitoring UAV

Depei Zhang Sr.; Yanhua Shao; Yanying Mei; Hongyu Chu; Xiaoqiang Zhang; Huayi Zhan; Yunbo Rao

doi:10.1117/12.2524219

6 May 2019 Using YOLO-based pedestrian detection for monitoring UAV

Depei Zhang Sr., Yanhua Shao, Yanying Mei, Hongyu Chu, Xiaoqiang Zhang, Huayi Zhan, Yunbo Rao

Proceedings Volume 11069, Tenth International Conference on Graphics and Image Processing (ICGIP 2018); 110693Y (2019) https://doi.org/10.1117/12.2524219
Event: Tenth International Conference on Graphic and Image Processing (ICGIP 2018), 2018, Chengdu, China

Abstract

Pedestrian detection (PD) is an important application domain in computer vision and pattern recognition. Conventional PD in real life scene is usually based on a fixed camera, which can detect and track the pedestrians in the monitoring region. However, when the pedestrian leaves the visible area of the fixed camera, it is usually difficult, if not impossible, to monitor the pedestrian. In response to the limitations of the conventional pedestrian detection application scenarios, a four-rotor unmanned aerial vehicle (UAV) system equipped with a high-definition (HD) camera is designed and implemented to detect human targets. Considering the size of human body in aerial image is small and easily to be occluded, we draw on the advanced research results in the field of target detection and propose a robust pedestrian detection method based on YOLO (You Only Look Once) network. The flow of the proposed approach is as follows. Firstly, the HD camera, which is installed on the monitoring UAV, is used for capturing images of the designated outdoor area. Secondly, image sequences are collected and processed using the airborne embedded NVIDIA Jason TX1 and Ubuntu as the core and operating system, respectively. Finally, YOLO is used to train the pedestrian classifier and perform the pedestrian detection. Experimental results show that our method has good detection results under the complicated conditions of detecting small-scale pedestrians and pedestrian occlusion.

Citation Download Citation

Depei Zhang Sr., Yanhua Shao, Yanying Mei, Hongyu Chu, Xiaoqiang Zhang, Huayi Zhan, and Yunbo Rao "Using YOLO-based pedestrian detection for monitoring UAV", Proc. SPIE 11069, Tenth International Conference on Graphics and Image Processing (ICGIP 2018), 110693Y (6 May 2019); https://doi.org/10.1117/12.2524219

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