@inproceedings{e1d3d89ffcc1403ebd494b183d46d601,
title = "Sparse representations and random projections for robust and cancelable biometrics",
abstract = "In recent years, the theories of Sparse Representation (SR) and Compressed Sensing (CS) have emerged as powerful tools for efficiently processing data in non-traditional ways. An area of promise for these theories is biometric identification. In this paper, we review the role of sparse representation and CS for efficient biometric identification. Algorithms to perform identification from face and iris data are reviewed. By applying Random Projections it is possible to purposively hide the biometric data within a template. This procedure can be effectively employed for securing and protecting personal biometric data against theft. Some of the most compelling challenges and issues that confront research in biometrics using sparse representations and CS are also addressed.",
keywords = "Cancelable biometrics, Face recognition, Iris recognition, Random projections, Sparse representations",
author = "Patel, {Vishal M.} and Rama Chellappa and Massimo Tistarelli",
year = "2010",
doi = "10.1109/ICARCV.2010.5707955",
language = "English (US)",
isbn = "9781424478132",
series = "11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010",
pages = "1--6",
booktitle = "11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010",
note = "11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010 ; Conference date: 07-12-2010 Through 10-12-2010",
}