Geometric feature selection for vehicle pose estimation on dynamic road scenes

This paper suggests classification and selection of features based on geometric properties to accomplish more accurate visual odometry. We apply billboard sweep stereo algorithm and the homogeneous disparity representation to obtain several categories of geometric labels. And we combine the classes to estimate more accurate vehicle pose. In the experiments, the distant features are useful for estimating vehicle orientation and the features on the ground plane are proper for estimating vehicle position especially in crowded road scenes.