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<p>The accuracy and the dependence on parameters of a general scheme for the analysis of time-varying image sequences are discussed. The approach is able to produce vector fields from which it is possible to recover 3-D motion parameters such as time-to-collision and angular velocity. The numerical stability of the computed optical flow and the dependence of the recovery of 3-D motion parameters on spatial and temporal filtering is investigated. By considering optical flows computed on subsampled images or along single scanlines, it is also possible to recover 3-D motion parameters from reduced optical flows. An adequate estimate of time-to-collision can be obtained from sequences of images with spatial resolution reduced to 128*128 pixels or from sequences of single scanlines passing near the focus of expansion. The use of Kalman filtering increases the accuracy and the robustness of the estimation of motion parameters. The proposed approach seems to be able to provide not only a theoretical background but also practical tools that are adequate for the analysis of time-varying image sequences.</p>
3D motion parameter recovery; spatial filtering; optical flow; time-varying image sequences; time-to-collision; angular velocity; temporal filtering; subsampled images; scanlines; Kalman filtering; 128 pixels; 16384 pixels; filtering and prediction theory; image sequences; motion estimation; optical information processing; parameter estimation

V. Torre, E. De Micheli and S. Uras, "The Accuracy of the Computation of Optical Flow and of the Recovery of Motion Parameters," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 15, no. , pp. 434-447, 1993.
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