@inproceedings{62900e5121354061a988fe722165c598,
title = "Using sparse regression to learn effective projections for face recognition",
abstract = "We explore sparse regression for effective feature selection and classification in face identity and expression recognition. We argue that sparse regression in pixel space is inappropriate. We propose instead a method which combines the virtues of sparse regression with projection methods such as PCA and FDA. The method can learn a sparse set of discriminative projections and increase recognition accuracy beyond that achievable by FDA.We demonstrate this by performance comparisons on three face data sets.",
author = "Xi, {Yongxin Taylor} and Ramadge, {Peter J.}",
year = "2009",
doi = "10.1109/ICIP.2009.5413913",
language = "English (US)",
isbn = "9781424456543",
series = "Proceedings - International Conference on Image Processing, ICIP",
publisher = "IEEE Computer Society",
pages = "3333--3336",
booktitle = "2009 IEEE International Conference on Image Processing, ICIP 2009 - Proceedings",
address = "United States",
note = "2009 IEEE International Conference on Image Processing, ICIP 2009 ; Conference date: 07-11-2009 Through 10-11-2009",
}