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<p><b>Abstract</b>—Synthetic discriminant functions have been used to locate objects irrespective of distortions and to estimate the extent of the distortion. It was recognized from the beginning that accurate estimates are only possible provided the training set is constructed carefully. In this paper, we obtain conditions that will ensure the accuracy of the estimates. The conditions also suggest efficient ways of constructing the training sets and the results are extended to a wide class SDF-type filters. The theoretical results are illustrated with (idealized) examples and are also applied to the more realistic problem of accurate facial location.</p>
Synthetic discriminant functions, synthetic estimation filters, facial location.

N. Muller and B. Herbst, "On the Use of SDF-Type Filters for Distortion Parameter Estimation," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 24, no. , pp. 1521-1528, 2002.
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