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Rolf P. Würtz

Organic Computing Methods for Face Recognition

Automatic face recognition is a slowly maturing and economically highly important technology, which still falls short of the high expectations set on it. The variation in images taken from the same person makes face recognition systems difficult to design — it is impossible to explicitly code all variability. Successful systems have relied heavily on the principle of self-organizing many fragile cues to arrive at a robust decision and have been built by learning from biological systems. The paper describes the techniques of elastic bunch graph matching as a hierarchical integration of image pixels into Gabor responses, jets, graphs, and bunch graphs. Beside face recognition, these concepts are used for face classification learned from examples. It is attempted to develop them further to reach a complete parameterization of all faces. Methods for more general object recognition using the same Organic Computing principles are outlined and include the concept of end-stopped cells as corner detectors.

it – Information Technology (vormals it+ti), Oldenbourg Wissenschaftsverlag

Print ISSN: 1611-2776
Volume: 47, 04/2005
Pages: 207 - 211

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