The main goal of this research is to test how well existing feature extraction, matching and motion estimation algorithms (with appropriate modification) work on outdoor scenes. For this purpose, a careful calibrated image sequence data base has been created. The data used for the results reported in this paper consists of a sequence of 24 stereo images of an outdoor scene containing a moving truck with stationary background. Two motion estimation methods using feature correspondences were applied in the data: point correspondences over two stereo image pairs and line correspondences over three monocular images. In spite of the large values of the range to baseline ration (10:1) and the range to focal length ration (1000:1), the estimated rotation parameters are reasonably accurate (10-20% errors) in both methods. Although the translation estimates in the monocular method are large, the translation errors in the stereo method are around 1 meter, and are mainly due to image sampling.