Abstract
This paper presents a stereo-based system for measuring traffic on motorways. To achieve real-time performance, the system exploits a decentralized architecture composed of a pair of smart cameras fixed over the road and connected via network to an embedded industrial PC on the side of the road. Different features (Harris corners and edges) are detected on the two images and matched together with local matching algorithm. The resulting 3D points cloud is processed by maximum spanning tree clustering algorithm to group the points into vehicle objects. Bounding boxes are defined for each detected object, giving an approximation of the vehicles 3D sizes. The system presented here has been validated manually and gives over 90% of good detection accuracy at 20-25 frames/s.
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Houben, Q., Czyz, J., Tocino Diaz, J.C., Debeir, O., Warzee, N. (2009). Feature-Based Stereo Vision Using Smart Cameras for Traffic Surveillance. In: Fritz, M., Schiele, B., Piater, J.H. (eds) Computer Vision Systems. ICVS 2009. Lecture Notes in Computer Science, vol 5815. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04667-4_15
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DOI: https://doi.org/10.1007/978-3-642-04667-4_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04666-7
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