Generalization From a Single View in Face Recognition

Lando, Maria and Edelman, Shimon (1995) Generalization From a Single View in Face Recognition. [Preprint]

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We describe a computational model of face recognition, which generalizes from single views of faces, by taking advantage of prior experience with other faces, seen under a wider range of viewing conditions. The model represents face images by vectors of activities of graded overlapping receptive fields (RFs). It relies on high spatial frequency information to estimate the viewing conditions, which are then used to normalize (via a transformation specific for faces), and identify, the low spatial frequency representation of the input. The class-specific transformation approach allows the model to replicate a series of psychophysical findings on face recognition, and constitutes an advance over current face recognition methods, which are incapable of generalization from a single example.

Item Type:Preprint
Subjects:Psychology > Cognitive Psychology
ID Code:576
Deposited By: Edelman, Shimon
Deposited On:18 Nov 1997
Last Modified:11 Mar 2011 08:54


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