Vehicle trajectories are commonly used to analyse driving behaviour and traffic safety. Traditional blob detection methods are limited in providing the accurate locations of vehicles when these are monitored from a low position. The authors propose a novel method of vehicle detection by utilising the projection line between the vehicle side and the ground plane. The line, which is extremely close to the surface of the road plane, provides location and orientation information. Therefore the authors’ method further locates vehicles by matching the two-dimensional (2D) model with the vehicle bottom by using a projection line and a projective transformation matrix. The model-based tracking method is used to track the detected vehicles, and a Kalman filter is combined to predict the locations of vehicles. The output is a set of microscopic parameters which include vehicle ID, trajectory, velocity, acceleration, orientation and angular speed, respectively. The experimental results are acceptable in terms of vehicle detection, vehicle tracking, trajectory extraction and computation time, respectively.
Vehicle trajectory extraction by simple two-dimensional model matching at low camera angles in intersection
IET Intelligent Transport Systems ; 8 , 7 ; 631-638
2014-11-01
8 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
vehicle ID , driving behaviour analysis , road plane , Kalman filters , microscopic parameters , 2D model , traffic safety , model-based tracking method , projection line , road traffic , vehicle detection method , feature extraction , two-dimensional model matching , object detection , detected vehicle tracking , road vehicles , road safety , ground plane , blob detection methods , object tracking , angular speed , vehicle trajectory extraction , vehicle side , at low camera angles , cameras , Kalman filter , orientation information
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