@conference {15921,
	title = {Sparse representations and Random Projections for robust and cancelable biometrics},
	booktitle = {Control Automation Robotics Vision (ICARCV), 2010 11th International Conference on},
	year = {2010},
	month = {2010/12//},
	pages = {1 - 6},
	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 biome $\#$x0301;trie identification. In this paper, we review the role of sparse representation and CS for efficient biome $\#$x0301;trie identification. Algorithms to perform identification from face and iris data are reviewed. By applying Random Projections it is possible to purposively hide the biome $\#$x0301;trie data within a template. This procedure can be effectively employed for securing and protecting personal biome $\#$x0301;trie 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 = {Biometric identification, Cancelable Biometrics, Compressed sensing, face data, face recognition, iris data, iris recognition, personal biometric data, Random Projections, robust biometrics, sparse representations},
	doi = {10.1109/ICARCV.2010.5707955},
	author = {Patel, Vishal M. and Chellapa, Rama and Tistarelli,M.}
}
