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<p>A straightforward method is presented for the determination of the optimal sensor exploration in the localization of a polyhedral object, whose geometry is known. Optimality is intended in the sense of the a posteriori covariance matrix of the object position and orientation parameters. The method consists in decomposing the problem into simpler subproblems, each one relative to a single planar face of the object. It requires reasonable processing time, i.e. comparable with the sensor activation time.</p>
image segmentation; image reconstruction; genetic algorithms; robust estimation; range image segmentation; image reconstruction; primitive parameters; homogeneous surface patch; residual consensus; RESC; compressed histogram method; best-fit surface parameters; planar surfaces; quadratic surfaces; least median squares method; genetic algorithm; random search

V. Caglioti, "Uncertainty Minimization in the Localization of Polyhedral Objects," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 16, no. , pp. 524-530, 1994.
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