Open AccessPedestrian detection based on one-stage YOLO algorithm
Author(s) -
Xia Zuo,
Jiaojun Li,
Jie Huang,
Fan Yang,
Tian Qiu,
Jun Yang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1871/1/012131
Subject(s) - pedestrian detection , stage (stratigraphy) , computer science , pedestrian , object detection , artificial intelligence , algorithm , pattern recognition (psychology) , engineering , transport engineering , paleontology , biology
Pedestrian detection is mostly used in autonomous driving scenarios, which require high real-time detection. Most of the existing algorithms are based on Two-Stage detection, with poor real-time performance. This paper proposes a pedestrian detection system based on One-Stage, and uses One-Stage-based YOLO-Tiny, YOLO and YOLO-SPP algorithms to test and analyze the system in the scene of detecting pedestrians of different sizes. The results show that YOLO and YOLO-SPP have high average confidence, and YOLO-Tiny has a fast detection speed, which is suitable for fast detection scenarios.