CASIA OpenIR  > 模式识别国家重点实验室  > 模式分析与学习
A Saliency-Based Cascade Method for Fast Traffic Sign Detection
Wang Dongdong1; Yue Shigang2; Xu Jiawei2; Hou Xinwen1; Liu Cheng-Lin1
2015-06
Conference Name2015 IEEE Intelligent Vehicles Symposium
Source Publication2015 IEEE Intelligent Vehicles Symposium (IV)
Pages180 - 185
Conference Date2015-6-28-2015-7-1
Conference Place韩国首尔
AbstractWe propose a cascade method for fast and accurate traffic sign detection. The main feature of the method is that mid-level saliency test is used to efficiently and reliably eliminate background windows. Fast feature extraction is adopted in the subsequent stages for rejecting more negatives. Combining with neighbor scales awareness in window search, the proposed method runs at 3~5 fps for high resolution (1360×800) images, 2~7 times as fast as most state-of-the-art methods. Compared with them, the proposed method yields competitive performance on prohibitory signs while sacrifices performance moderately on danger and mandatory signs.
KeywordTraffic Sign Detection Cascade Neighbor Scale Awareness
Subject Area模式识别与智能系统
DOI10.1109/IVS.2015.7225683
Indexed ByEI
Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/11750
Collection模式识别国家重点实验室_模式分析与学习
Corresponding AuthorWang Dongdong
Affiliation1.中科院自动化研究所
2.英国林肯大学
Recommended Citation
GB/T 7714
Wang Dongdong,Yue Shigang,Xu Jiawei,et al. A Saliency-Based Cascade Method for Fast Traffic Sign Detection[C],2015:180 - 185.
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