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In this paper we present a new method which enables a robust calculation of the LDA classification rule, thus making the recognition of objects under non-ideal conditions possible, i.e., in situations when objects are occluded or they appear on a varying background, or when their images are corrupted by outliers. The main idea behind the method is to translate the task of calculating the LDA classification rule into the problem of determining the coefficients of an augmented generative modeldoi:10.1109/cvprw.2003.10089 dblp:conf/cvpr/FidlerL03 fatcat:l3pvpchhqvfhhhohniimnndvxa