Vision-Based Traffic Sign Detection and Analysis for Intelligent Driver Assistance Systems: Perspectives and Survey

被引:395
作者
Mogelmose, Andreas [1 ]
Trivedi, Mohan Manubhai [2 ]
Moeslund, Thomas B. [1 ]
机构
[1] Aalborg Univ, Visual Anal People Lab, Aalborg, Denmark
[2] Univ Calif San Diego, Comp Vis & Robot Res Lab, La Jolla, CA 92093 USA
关键词
Active safety; human-centered computing; machine learning; machine vision; object detection; RADIAL SYMMETRY; RECOGNITION; CLASSIFICATION; ALGORITHMS; VEHICLE;
D O I
10.1109/TITS.2012.2209421
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
In this paper, we provide a survey of the traffic sign detection literature, detailing detection systems for traffic sign recognition (TSR) for driver assistance. We separately describe the contributions of recent works to the various stages inherent in traffic sign detection: segmentation, feature extraction, and final sign detection. While TSR is a well-established research area, we highlight open research issues in the literature, including a dearth of use of publicly available image databases and the over-representation of European traffic signs. Furthermore, we discuss future directions of TSR research, including the integration of context and localization. We also introduce a new public database containing U.S. traffic signs.
引用
收藏
页码:1484 / 1497
页数:14
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