Summary of Pedestrian Traffic Statistics Research

被引：0
作者：
Sheng, Jian [1 ,2 ,3 ]
Zhang, Zhi [1 ,2 ,3 ]
机构：
[1] Wuhan Univ Sci & Technol, Coll Comp Sci & Technol, Wuhan 430065, Hubei, Peoples R China
[2] Hubei Prov Key Lab Intelligent Informat Proc & Re, Wuhan 430065, Hubei, Peoples R China
[3] Wuhan Univ Sci & Technol, Big Data Sci & Engn Res Inst, Wuhan 430065, Hubei, Peoples R China
来源：
PROCEEDINGS OF THE 15TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA 2020) | 2020年
关键词：
Pedestrian Flow Statistics; Feature Extraction; Target Detection and Recognition; Target Count;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
As an important research direction in the field of computer vision and intelligent security, pedestrian traffic statistics have received more and more attention from the industry. This paper reviews the research on the important aspects of pedestrian flow statistics technology: feature extraction, target detection and pedestrian counting. Firstly, the typical methods of feature extraction are classified and compared according to the characteristics, and then the research on target detection and recognition is carried out. After summarizing, the pedestrian target count is introduced from the traditional method and the deep learning method respectively, and finally the future development is expected.
引用
收藏
页码：43 / 47
页数：5
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