This paper presents a novel approach for extracting characteristic parts of a face. Rather than finding a priori specified features such as nose, eyes, mouth or others, the proposed approach is aimed at extracting from a face the most distinguishing or dissimilar parts with respect to another given face, i. e. at "finding differences" between faces. This is accomplished by feeding a binary classifier by a set of image patches, randomly sampled from the two face images, and scoring the patches (or features) by their mutual distances. In order to deal with the multi-scale nature of natural facial features, a local space-variant sampling has been adopted. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Bicego, M., Grosso, E., & Tistarelli, M. (2005). On finding differences between faces. In Lecture Notes in Computer Science (Vol. 3546, pp. 329–338). Springer Verlag. https://doi.org/10.1007/11527923_34
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