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E. De Micheli, V. Torre, S. Uras, "The Accuracy of the Computation of Optical Flow and of the Recovery of Motion Parameters," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 15, no. 5, pp. 434447, May, 1993.  
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@article{ 10.1109/34.211464, author = {E. De Micheli and V. Torre and S. Uras}, title = {The Accuracy of the Computation of Optical Flow and of the Recovery of Motion Parameters}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {15}, number = {5}, issn = {01628828}, year = {1993}, pages = {434447}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.211464}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Pattern Analysis and Machine Intelligence TI  The Accuracy of the Computation of Optical Flow and of the Recovery of Motion Parameters IS  5 SN  01628828 SP434 EP447 EPD  434447 A1  E. De Micheli, A1  V. Torre, A1  S. Uras, PY  1993 KW  3D motion parameter recovery; spatial filtering; optical flow; timevarying image sequences; timetocollision; 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 VL  15 JA  IEEE Transactions on Pattern Analysis and Machine Intelligence ER   
The accuracy and the dependence on parameters of a general scheme for the analysis of timevarying image sequences are discussed. The approach is able to produce vector fields from which it is possible to recover 3D motion parameters such as timetocollision and angular velocity. The numerical stability of the computed optical flow and the dependence of the recovery of 3D 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 3D motion parameters from reduced optical flows. An adequate estimate of timetocollision 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 timevarying image sequences.
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