Real-time vehicle matching for multi-camera tunnel surveillance
Autor: | Jorge Oswaldo Nino Castaneda, Aleksandra Pižurica, Andres Frias-Velazquez, Wilfried Philips, Vedran Jelaca |
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Přispěvatelé: | Kehtarnavaz, Nasser, Carlsohn, Matthias F |
Jazyk: | angličtina |
Rok vydání: | 2011 |
Předmět: |
Matching (statistics)
traffic monitoring Technology and Engineering Radon transform Computer science business.industry feature extraction FEATURES Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Image processing Object recognition tunnel surveillance Computer vision Smart camera Artificial intelligence business Projection (set theory) |
Zdroj: | Proceedings of SPIE, the Society of Photo-Optical Instrumentation Engineers Real-Time Image and Video Processing |
ISSN: | 0277-786X |
Popis: | Tracking multiple vehicles with multiple cameras is a challenging problem of great importance in tunnel surveillance. One of the main challenges is accurate vehicle matching across the cameras with non-overlapping fields of view. Since systems dedicated to this task can contain hundreds of cameras which observe dozens of vehicles each, for a real-time performance computational efficiency is essential. In this paper, we propose a low complexity, yet highly accurate method for vehicle matching using vehicle signatures composed of Radon transform like projection profiles of the vehicle image. The proposed signatures can be calculated by a simple scan-line algorithm, by the camera software itself and transmitted to the central server or to the other cameras in a smart camera environment. The amount of data is drastically reduced compared to the whole image, which relaxes the data link capacity requirements. Experiments on real vehicle images, extracted from video sequences recorded in a tunnel by two distant security cameras, validate our approach. |
Databáze: | OpenAIRE |
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