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<p><b>Abstract</b>—We present a system for recognizing human faces from single images out of a large database containing one image per person. Faces are represented by <it>labeled graphs</it>, based on a Gabor wavelet transform. Image graphs of new faces are extracted by an elastic graph matching process and can be compared by a simple similarity function. The system differs from the preceding one [<ref rid="bibi07751" type="bib">1</ref>] in three respects. Phase information is used for accurate node positioning. Object-adapted graphs are used to handle large rotations in depth. Image graph extraction is based on a novel data structure, the <it>bunch graph</it>, which is constructed from a small set of sample image graphs.</p>
Face recognition, different poses, Gabor wavelets, elastic graph matching, bunch graph, ARPA/ARL FERET database, Bochum database.
Laurenz Wiskott, Christoph von der Malsburg, Jean-Marc Fellous, Norbert Krüger, "Face Recognition by Elastic Bunch Graph Matching", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 19, no. , pp. 775-779, July 1997, doi:10.1109/34.598235
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