Vision for Looking at Traffic Lights: Issues, Survey, and Perspectives
This paper presents the challenges that researchers must overcome in traffic light recognition (TLR) research and provides an overview of ongoing work. The aim is to elucidate which areas have been thoroughly researched and which have not, thereby uncovering opportunities for further improvement. An...
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| Veröffentlicht in: | IEEE transactions on intelligent transportation systems 2016-07, Vol.17 (7), p.1800-1815 |
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| container_title | IEEE transactions on intelligent transportation systems |
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| creator | Jensen, Morten Borno Philipsen, Mark Philip Mogelmose, Andreas Moeslund, Thomas Baltzer Trivedi, Mohan Manubhai |
| description | This paper presents the challenges that researchers must overcome in traffic light recognition (TLR) research and provides an overview of ongoing work. The aim is to elucidate which areas have been thoroughly researched and which have not, thereby uncovering opportunities for further improvement. An overview of the applied methods and noteworthy contributions from a wide range of recent papers is presented, along with the corresponding evaluation results. The evaluation of TLR systems is studied and discussed in depth, and we propose a common evaluation procedure, which will strengthen evaluation and ease comparison. To provide a shared basis for comparing TLR systems, we publish an extensive public data set based on footage from U.S. roads. The data set contains annotated video sequences, captured under varying light and weather conditions using a stereo camera. The data set, with its variety, size, and continuous sequences, should challenge current and future TLR systems. |
| doi_str_mv | 10.1109/TITS.2015.2509509 |
| format | Article |
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| ispartof | IEEE transactions on intelligent transportation systems, 2016-07, Vol.17 (7), p.1800-1815 |
| issn | 1524-9050 1558-0016 |
| language | eng |
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| source | IEEE Electronic Library (IEL) |
| subjects | active safety Cameras Color Computer vision Datasets driver assistance systems intelligent transportation system Intelligent transportation systems machine learning object detection Recognition Roads Shape Traffic light recognition Traffic signals Vehicles Video data Vision Weather conditions |
| title | Vision for Looking at Traffic Lights: Issues, Survey, and Perspectives |
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