Analysis of camera movements in stereo vision-based vehicle tracking

In an outdoor navigational environment, cameras of an autonomous vehicle or robot are subjected to uncontrollable movements relative to the vehicle or robot body. In this paper, the effect of such camera movements in stereo vision-based vehicle tracking systems is analyzed. It is shown how the computation of the range and heading angle of a lead vehicle is affected as a result of camera movements. The parameter space of the stereo system is divided into a controllable subspace consisting of the baseline and an uncontrollable subspace consisting of relative camera movements and the coordinates of a tracked point on the lead vehicle. The optimal baseline value is found by employing the mini-max and minimum mean-squared error estimators. The mini-max estimator is used to obtain the worst case performance while the minimum mean-squared estimator to obtain the average performance. Based on this analysis, it is shown how an optimal imaging geometry for a stereo vision-based tracking system can be designed in order to have the least amount of range and heading angle errors