Abstract
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.
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Bicego, M., Grosso, E., Tistarelli, M. (2005). On Finding Differences Between Faces. In: Kanade, T., Jain, A., Ratha, N.K. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2005. Lecture Notes in Computer Science, vol 3546. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527923_34
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DOI: https://doi.org/10.1007/11527923_34
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