Discriminative Face Recognition View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2003-06-24

AUTHORS

Florent Perronnin , Jean-Luc Dugelay

ABSTRACT

A novel probabilistic deformable model of face mapping was recently introduced and successfully applied to automatic person identification. In this paper, we consider the use of discrimination to improve the performance of this system. It is possible to introduce discriminative information at two different levels: 1) in the face representations and 2) in the deformable model used to match face images. We explore both types of discrimination and compare them in terms of performance and computational complexity. Results are presented on the FERET face database for a face identification task and show that, in this framework and for the discriminative techniques that were considered, the discrimination of the deformable model should be preferred and can result in a 25–40% relative error rate reduction compared to the baseline system. More... »

PAGES

446-454

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/3-540-44887-x_53

DOI

http://dx.doi.org/10.1007/3-540-44887-x_53

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1004288319


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