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A recursive algorithm for estimating the three-dimensional trajectory and structure of a moving rigid object in an image sequence has been previously developed by Broida, Chandrashekhar, and Chellappa . Since then, steady advances have occurred in the calculation of optical flow. This work improves 3D motion trajectory and structure estimation by incorporating optical flow into the estimation framework. The new solution combines optical flow and feature point measurements and determines their statistical relationship. The feasibility of a hybrid feature point/optical flow algorithm, demonstrated through detailed simulation on synthetic and real image sequences, significantly lowers bias and mean squared error in trajectory estimation over the feature-based approach.