CASIA OpenIR  > 模式识别国家重点实验室  > 机器人视觉
Towards Real-Time Traffic Sign Detection and Classification
Yang, Yi1; Luo, Hengliang1; Xu, Huarong2; Wu, Fuchao1
AbstractTraffic sign recognition plays an important role in driver assistant systems and intelligent autonomous vehicles. Its real-time performance is highly desirable in addition to its recognition performance. This paper aims to deal with real-time traffic sign recognition, i.e., localizing what type of traffic sign appears in which area of an input image at a fast processing time. To achieve this goal, we first propose an extremely fast detection module, which is 20 times faster than the existing best detection module. Our detection module is based on traffic sign proposal extraction and classification built upon a color probability model and a color HOG. Then, we harvest from a convolutional neural network to further classify the detected signs into their subclasses within each superclass. Experimental results on both German and Chinese roads show that both our detection and classification methods achieve comparable performance with the state-of-the-art methods, with significantly improved computational efficiency.
KeywordTraffic Sign Detection Traffic Sign Recognition Real-time Color Probability Model
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
Funding OrganizationNational Natural Science Foundation of China(61375043 ; Education Bureau of Fujian Province, China(JK2011044) ; Xiamen Science and Technology Plan through the University Innovation Project(3502Z20131158) ; 61273290)
WOS Research AreaEngineering ; Transportation
WOS SubjectEngineering, Civil ; Engineering, Electrical & Electronic ; Transportation Science & Technology
WOS IDWOS:000379908100021
Citation statistics
Cited Times:27[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
2.Xiamen Univ Technol, Xiamen 361024, Peoples R China
Recommended Citation
GB/T 7714
Yang, Yi,Luo, Hengliang,Xu, Huarong,et al. Towards Real-Time Traffic Sign Detection and Classification[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2016,17(7):2022-2031.
APA Yang, Yi,Luo, Hengliang,Xu, Huarong,&Wu, Fuchao.(2016).Towards Real-Time Traffic Sign Detection and Classification.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,17(7),2022-2031.
MLA Yang, Yi,et al."Towards Real-Time Traffic Sign Detection and Classification".IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 17.7(2016):2022-2031.
Files in This Item: Download All
File Name/Size DocType Version Access License
TITS-2016-3-Towards (3538KB)期刊论文作者接受稿开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Yang, Yi]'s Articles
[Luo, Hengliang]'s Articles
[Xu, Huarong]'s Articles
Baidu academic
Similar articles in Baidu academic
[Yang, Yi]'s Articles
[Luo, Hengliang]'s Articles
[Xu, Huarong]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Yang, Yi]'s Articles
[Luo, Hengliang]'s Articles
[Xu, Huarong]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: TITS-2016-3-Towards Real-Time Traffic Sign Detection.pdf
Format: Adobe PDF
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.