@inproceedings{ff2358b02ae341c3b0a68577e67b6fc5,
title = "Sparse representation and least squares-based classification in face recognition",
abstract = "In this paper we present a novel approach to face recognition. We propose an adaptation and extension to the state-of-the-art methods in face recognition, such as sparse representation-based classification and its extensions. Effectively, our method combines the sparsity-based approaches with additional least-squares steps and exhitbits robustness to outliers achieving significant performance improvement with little additional cost. This approach also mitigates the need for a large number of training images since it proves robust to varying number of training samples.",
keywords = "Face recognition, classification, sparse representation",
author = "Michael Iliadis and Leonidas Spinoulas and Berahas, {Albert S.} and Haohong Wang and Katsaggelos, {Aggelos K.}",
note = "Publisher Copyright: {\textcopyright} 2014 EURASIP.; 22nd European Signal Processing Conference, EUSIPCO 2014 ; Conference date: 01-09-2014 Through 05-09-2014",
year = "2014",
month = nov,
day = "10",
language = "English (US)",
series = "European Signal Processing Conference",
publisher = "European Signal Processing Conference, EUSIPCO",
pages = "526--530",
booktitle = "2014 Proceedings of the 22nd European Signal Processing Conference, EUSIPCO 2014",
}