A robust approach is presented to estimating motion and structure from image sequences. The approach consists of two steps. The first step is estimating the motion parameters using a robust linear algorithm that gives a closed-form solution for motion parameters and scene structure. The second step is improving the results from the linear algorithm using maximum-likelihood estimation. An algorithm using point correspondences from monocular images is discussed in detail and experimented with. An algorithm using line correspondences is briefly discussed. The simulations show that maximum-likelihood estimation achieves remarkable improvement over the preliminary estimates given by the linear algorithm. The algorithm is also tested on images of real scenes from automatically computed displacement field. The proposed approach is independent of the exact tokens used to establish correspondences, e.g. displacement flow, optical flow, or discrete features. Two or more types of tokens may be used, for monocular or binocular images.