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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.
Zhu et al. (Thu,) studied this question.