Stereo Visual Tracking Within Structured Environments for Measuring Vehicle Speed

We present a novel visual tracking method for measuring the speed of a moving vehicle within a structured environment using stationary stereo cameras. In the proposed method, visual stereo tracking and motion estimation in 3-D are integrated within the framework of particle filtering. The visual tracking processes in the two views are coupled with each other since they are dependent upon the same 3-D motion and correlated in the observations. Considering that the vehicle´s motion is physically constrained by the environment, we further utilize the path constraint reconstructed from stereo views to reduce the uncertainty about the vehicle´s motion and improve the accuracy for both tracking and speed measuring. The proposed method overcomes the challenges arising from the limitation of depth accuracy in a long-range stereo, and the experiments on the synthetic and real-world sequences have demonstrated its effectiveness and accuracy in both the tracking performance and the speed measurement.