On board video analysis has attracted a lot of interest over the two last decades with as main goal to improve safety by
detecting obstacles or assisting the driver. Our study aims at providing a real-time understanding of the urban road
traffic. Considering a video camera fixed on the front of a public bus, we propose a cost-effective approach to estimate
the speed of the vehicles on the adjacent lanes when the bus operates on a dedicated lane. We work on 1-D segments
drawn in the image space, aligned with the road lanes. The relative speed of the vehicles is computed by detecting and
tracking features along each of these segments. The absolute speed can be estimated from the relative speed if the camera
speed is known, e.g. thanks to an odometer and/or GPS. Using pre-defined speed thresholds, the traffic can be classified
into different categories such as 'fluid', 'congestion' etc. The solution offers both good performances and low computing
complexity and is compatible with cheap video cameras, which allows its adoption by city traffic management authorities.
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