Traffic police gesture recognition based on Faster R-CNN and fuzzy matching algorithm

被引：0
|
作者：
Zhou Q. [1 ]
Wang S.F. [1 ]
Wang Y.Q. [2 ]
Zhang J.Y. [1 ]
机构：
[1] College of Transportation, Shandong University of Science and Technology, Qingdao
[2] Zibo City Planning and Design Research Institute Company Limited, No. 15, Renmin West Road, Zhangdian District, Shandong, Zibo
来源：
Advances in Transportation Studies | 2023年 / 60卷
关键词：
decomposition action; Faster R-CNN; fuzzy matching; image recognition; traffic police gestures;
D O I：
10.53136/979122180742410
中图分类号：
学科分类号：
摘要：
For autonomous vehicles, when encountering traffic accidents or bad weather and other complex situations that made the traffic signal stop working, recognizing the command of traffic police gesture was very important. A new method of traffic police gesture recognition was proposed. First, the traffic police gestures were decomposed into “key actions” and “transition actions” based on the motion characteristics, Secondly, using Faster R-CNN and fuzzy matching the gesture recognition model was build. Faster R-CNN was used to extract the features of decomposed actions for image recognition; a fuzzy matching method was built to match gestures based on the recognition of decomposed actions. Finally, the recognition experiment was executed, as for common traffic police gesture, the result showed that the new proposed method was effective. © 2023, Aracne Editrice. All rights reserved.
引用
收藏
页码：159 / 170
页数：11
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