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<p>Concerns the estimation of the motion parameters of a rigid body from noisy point matches made on perspective views. A minimization problem which permits relatively robust parameter estimation and helps overcome poor zoom estimation when the field-of-view is small is formulated. It is assumed that the motion has a small rotary component, interframe differences are small, and the errors in the system are due to independently distributed errors in the components of the displacement vectors. A fast procedure for minimization is exposited, in which the parameter set is partitioned and conditional generalized least-squares formulas identified. Recursive application of these provides the search space for the minimization problem. Comparative results are presented using simulated data and displacement vectors obtained from an intensity-based matching algorithm.</p>
parameter set partitioning; recursive methods; iterated estimation; noisy displacement vectors; motion parameters; noisy point matches; perspective views; minimization; robust parameter estimation; rotary component; interframe differences; independently distributed errors; conditional generalized least-squares formulas; iterative methods; minimisation; noise; parameter estimation; pattern recognition; picture processing

J. Aisbett, "An Iterated Estimation of the Motion Parameters of a Rigid Body from Noisy Displacement Vectors," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 12, no. , pp. 1092-1098, 1990.
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