In the last years the huge evolution of digital photography lead to an increasing interest in developing
algorithms for indexing and classifying collections of digital images. This paper presents an automatic
system for organizing and browsing through consumer digital image collections using the persons in the
images as patterns. In order to implement such an automatic system we have to detect and classify the
people in the images according to their similarities. For this we employ algorithms for face detection,
face recognition and additional methods to cope with large variations that are usually present in
consumer images. These additional methods includes using more than one type of classifiers for face
recognition and also using additional information about the person characteristics extracted from other
region than the face. This additional information will be more robust to factors that influence the
accuracy of classical face recognition systems when working with consumer images. The proposed
system was tested using a typical consumer image collection and practical applications using the system
are presented in the end.
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