Real-Time Traffic Sign Recognition Based on Efficient CNNs in the Wild

doi:10.1109/TITS.2018.2843815

CORC > 合肥物质科学研究院 > 中国科学院合肥物质科学研究院 > 中科院固体物理研究所

	Real-Time Traffic Sign Recognition Based on Efficient CNNs in the Wild
	Li, Jia 2; Wang, Zengfu 1,3
刊名	IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
	2019-03-01
卷号	20 期号:3 页码:975-984
关键词	Traffic sign recognition Faster R-CNN localization refinement efficient CNN
ISSN号	1524-9050
DOI	10.1109/TITS.2018.2843815
通讯作者	Wang, Zengfu(zfwang@ustc.edu.cn)
英文摘要	Both unmanned vehicles and driver assistance systems require solving the problem of traffic sign recognition. A lot of work has been done in this area, but no approach has been presented to perform the task with high accuracy and high speed under various conditions until now. In this paper, we have designed and implemented a detector by adopting the framework of faster R-convolutional neural networks (CNN) and the structure of MobileNet. Here, color and shape information have been used to refine the localizations of small traffic signs, which are not easy to regress precisely. Finally, an efficient CNN with asymmetric kernels is used to be the classifier of traffic signs. Both the detector and the classifier have been trained on challenging public benchmarks. The results show that the proposed detector can detect all categories of traffic signs. The detector and the classifier proposed here are proved to be superior to the state-of-the-art method. Our code and results are available online.
资助项目	National Natural Science Foundation of China[61472393]
WOS关键词	ALGORITHMS
WOS研究方向	Engineering ; Transportation
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000460758300015
资助机构	National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.hfcas.ac.cn:8080/handle/334002/42372]
专题	合肥物质科学研究院_中科院固体物理研究所
通讯作者	Wang, Zengfu
作者单位	1.Natl Engn Lab Speech & Language Informat Proc, Hefei 230026, Anhui, Peoples R China 2.Univ Sci & Technol China, Dept Automat, Hefei 230026, Anhui, Peoples R China 3.Chinese Acad Sci, Inst Intelligent Machines, Hefei 230031, Anhui, Peoples R China
推荐引用方式 GB/T 7714	Li, Jia,Wang, Zengfu. Real-Time Traffic Sign Recognition Based on Efficient CNNs in the Wild[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2019,20(3):975-984.
APA	Li, Jia,&Wang, Zengfu.(2019).Real-Time Traffic Sign Recognition Based on Efficient CNNs in the Wild.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,20(3),975-984.
MLA	Li, Jia,et al."Real-Time Traffic Sign Recognition Based on Efficient CNNs in the Wild".IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 20.3(2019):975-984.