access icon free Vehicle trajectory extraction by simple two-dimensional model matching at low camera angles in intersection

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.

Inspec keywords: object detection; object tracking; road vehicles; road safety; feature extraction; cameras; Kalman filters; road traffic

Other keywords: angular speed; microscopic parameters; Kalman filter; projection line; driving behaviour analysis; vehicle ID; blob detection methods; vehicle side; detected vehicle tracking; ground plane; at low camera angles; road plane; traffic safety; vehicle detection method; vehicle trajectory extraction; 2D model; orientation information; model-based tracking method; two-dimensional model matching

Subjects: Computer vision and image processing techniques; Image sensors; Filtering methods in signal processing; Image recognition; Traffic engineering computing

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