A system for automatic face recognition
The automatic detection of person's identity is a very interesting issue both in social and industrial environments. In this paper a system for automatic face recognition from images of faces is presented. The proposed approach is based on an hybrid iconic approach, where a first recognition score is obtained by matching a person's face against an eigen-space obtained from an image ensemble of known indivisuals. The identity is verified by computing the correlation of the gray level histograms of the new face image and the one in the database.
A selective attentional mechanism is applied to reduce the amount of information needed to describe a database of objects. This is accomplished both at the task level, by performing planned fixations, and at the sensor level, by adopting a space-variant sampling of the images.
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