publication . Part of book or chapter of book . Conference object . 2009

A Classification Framework for Large-Scale Face Recognition Systems

Name: A Classification Framework for Large-Scale Face Recognition Systems
Keywords: TA1650

Ziheng Zhou; Farzin Deravi; Samuel Chindaro;

Open Access

Published: 01 Jun 2009

Publisher: Springer Berlin Heidelberg

Country: United Kingdom

Summary

Abstract

This paper presents a generic classification framework for large-scale face recognition systems. Within the framework, a data sampling strategy is proposed to tackle the data imbalance when image pairs are sampled from thousands of face images for preparing a training dataset. A modified kernel Fisher discriminant classifier is proposed to make it computationally feasible to train the kernel-based classification method using tens of thousands of training samples. The framework is tested in an open-set face recognition scenario and the performance of the proposed classifier is compared with alternative techniques. The experimental results show that the classifica...

doi: 10.1007/978-3-642-01793-3_35

Subjects

ACM Computing Classification System: ComputingMethodologies_PATTERNRECOGNITION

free text keywords: TA1650, Kernel (linear algebra), Fisher kernel, Linear discriminant analysis, Data imbalance, Facial recognition system, Classifier (linguistics), Artificial intelligence, business.industry, business, Classification methods, Pattern recognition, Machine learning, computer.software_genre, computer, Kernel Fisher discriminant analysis, Computer science

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