Vision based three-dimensional vehicle motion detection by minimizing nonlinear functions

This paper presents a method to accurately determine the three-dimensional motion of a vehicle based on image pairs acquired with a stereo system. The basic idea is to express the relationship between correspondent features that belong to non moving objects in successive frames as a nonlinear function of rotation and translation parameters. Minimizing the distance between the previously mentioned parametric correspondences and the correspondences computed using optical flow methods, leads us to accurate estimation of the motion parameters.