Traffic Sign Recognition Using a Multi-Task Convolutional Neural Network

doi:10.1109/TITS.2017.2714691

	Traffic Sign Recognition Using a Multi-Task Convolutional Neural Network
	Luo, Hengliang1,2 ; Yang, Yi 1; Tong, Bei1 ; Wu, Fuchao1 ; Fan, Bin1
发表期刊	IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
	2018-04-01
卷号	19 期号:4 页码:1100-1111
文章类型	Article
摘要	Although traffic sign recognition has been studied for many years, most existing works are focused on the symbol-based traffic signs. This paper proposes a new data-driven system to recognize all categories of traffic signs, which include both symbol-based and text-based signs, in video sequences captured by a camera mounted on a car. The system consists of three stages, traffic sign regions of interest (ROIs) extraction, ROIs refinement and classification, and post-processing. Traffic sign ROIs from each frame are first extracted using maximally stable extremal regions on gray and normalized RGB channels. Then, they are refined and assigned to their detailed classes via the proposed multi-task convolutional neural network, which is trained with a large amount of data, including synthetic traffic signs and images labeled from street views. The post-processing finally combines the results in all frames to make a recognition decision. Experimental results have demonstrated the effectiveness of the proposed system.
关键词	Traffic Sign Detection Traffic Sign Classification Convolutional Neural Network Multi-task Learning
WOS标题词	Science & Technology ; Technology
DOI	10.1109/TITS.2017.2714691
关键词[WOS]	CLASSIFICATION
收录类别	SCI
语种	英语
项目资助者	National High Technology Research and Development Program of China(2015AA124102) ; National Natural Science Foundation of China(61375043) ; Beijing Natural Science Foundation(4142057)
WOS研究方向	Engineering ; Transportation
WOS类目	Engineering, Civil ; Engineering, Electrical & Electronic ; Transportation Science & Technology
WOS记录号	WOS:000429017300009
引用统计	被引频次：133[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/19824
专题	多模态人工智能系统全国重点实验室_机器人视觉
作者单位	1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
第一作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Luo, Hengliang,Yang, Yi,Tong, Bei,et al. Traffic Sign Recognition Using a Multi-Task Convolutional Neural Network[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2018,19(4):1100-1111.
APA	Luo, Hengliang,Yang, Yi,Tong, Bei,Wu, Fuchao,&Fan, Bin.(2018).Traffic Sign Recognition Using a Multi-Task Convolutional Neural Network.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,19(4),1100-1111.
MLA	Luo, Hengliang,et al."Traffic Sign Recognition Using a Multi-Task Convolutional Neural Network".IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 19.4(2018):1100-1111.

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