Effects of using a 3D model on the performance of vision algorithms

In previous work, we have shown how a 3D model can be built in real time and synchronized with the environment. This world model permits a robot to predict dynamics in its environment and classify behaviors. In this paper we evaluate the effect of such a 3D model on the accuracy and speed of various computer vision algorithms, including tracking, optical flow and stereo disparity. We report results based on the KITTI database and on our own videos.