A comparison of trajectories and vehicle dynamics acquired by high precision GPS and contemporary methods of digital image processing

Abstract

Vehicle trajectories from recorded video sequences—acquired by several contemporary methods of digital image processing—are compared with high-precision GPS data serving as a reference. The raw data has been created by driving some scenarios with a car equipped with several sensors, i.e. Differential GPS (DGPS), acceleration sensor, etc. At the same time, the car was recorded by a video camera system in order to derive trajectory data by computer vision methods. Thus, the car is tracked by an Extended Kalman Filter (EKF) preceded by a background estimator. To improve the accuracy of the tracking data it is combined with a model-based approach for object detection. This approach fits a 3-dimensional wire frame model of the car into the image. The paper presents the driving scenarios of the car, the implemented image processing methods and a quantitative evaluation of the extracted trajectories obtained by two different image processing methods. Accuracy and precision of the methods are determined by comparing their results with the DGPS reference data of the car.