Fully automatic video and image analysis from traffic monitoring cameras is a fast-emerging field based on computer vision techniques with a growing impact on Intelligent Transport Systems (ITS).
Indeed the decreasing hardware cost and, therefore, the increasing deployment of cameras and embedded systems have opened a wide application field for video analytics both in urban and highway scenarios. It can be envisaged that several monitoring objectives such as congestion, traffic rule violation, and vehicle interaction can be targeted using cameras that were typically originally installed for human operators .
On highways, systems for the detection and classification of vehicles have successfully been using classical visual surveillance techniques such as background estimation and motion tracking for some time. Nowadays existing methodologies have good performance also in case of inclement weather and are operational 24/7. On the converse, the urban domain is less explored and more challenging with respect to traffic density, lower camera angles that lead to a high degree of occlusion and the greater variety of street users. Methods from object categorization and 3-D modelling have inspired more advanced techniques to tackle these ...