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This project aims at developing an automatic road inventory system (ARIS) that detects, recognizes, and tracks traffic signs. ARIS takes video sequences which are acquired for the target roads by, e.g, low cost cameras embedded GPS (Global Positioning System) information. Outcomes of ARIS are expected to be all meaning traffic signs that are first detected and then recognized into the given sign categories. Furthermore, these signs are tracked along the road with their accurate positions that are calculated based on the recorded GPS information.
The project goal is to address the challenge by exploiting several combined computer vision techniques. Furthermore, the ARIS system is able to be enhanced by taking multiple cameras, which acquire the data, into account.
References
- S. Houben, J. Stallkamp, J. Salmen, M. Schlipsing, and C. Igel, "Detection of Traffic Signs in Real-World Images: The German Traffic Sign Detection Benchmark," in International Joint Conference on Neural Networks 2013.
- The German traffic sign recognition benchmark and the German traffic sign detection benchmark, Institut für Neuroinformatik, Ruhr-Universität Bochum.
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