Traffic Police Pose Estimation Based on Multi-branch Network

被引：0

作者：

Wang, Haoran ^{[1
]}

Zhang, Qingyong ^{[1
]}

Du, Yuhao ^{[1
]}

Wang, Shixun ^{[1
]}

机构：

[1] Wuhan Univ Technol, Sch Automat, Wuhan, Hubei, Peoples R China

来源：

2018 CHINESE AUTOMATION CONGRESS (CAC) | 2018年

关键词：

traffic police gesture; CNN; pattern recognition;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

To precisely recognizing traffic police gesture, a two-branch multi-stage convolutional neural network (CNN) and an BP neural network (BPNN) classifier has been adopted to achieve the task of traffic police pose estimation in this paper. We simultaneously detect the human joints and associate body parts. When the detection work is done, a BPNN cascades after CNN and serve as a classifier. The experiment results show that traffic police-men's gestures are well recognized by this method.

引用

页码：1769 / 1773

页数：5

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