Obstacle detection by evaluation of optical flow fields from image sequences

In comparison with single images, image sequences contain information about the dynamic aspects of the recorded scene. Dynamic aspects play a crucial role in traffic scenarios, especially for the guidance of an autonomous vehicle. In this contribution, we present an approach for the detection of stationary obstacles and moving objects on the road of an autonomous vehicle by evaluation of optical flow fields from image sequences. It will be shown how two-dimensional optical flow fields can be interpreted to infer information about the three-dimensional environment if the camera is translating on a planar surface. Results obtained from investigations with three different approaches for the estimation of optical flow vectors are used to test the obstacle algorithm.