Sparse representations and Random Projections for robust and cancelable biometrics
| Title | Sparse representations and Random Projections for robust and cancelable biometrics |
| Publication Type | Conference Papers |
| Year of Publication | 2010 |
| Authors | Patel VM, Chellappa R, Tistarelli M |
| Conference Name | Control Automation Robotics Vision (ICARCV), 2010 11th International Conference on |
| Date Published | 2010/12// |
| Keywords | Biometric identification, Cancelable Biometrics, Compressed sensing, face data, face recognition, iris data, iris recognition, personal biometric data, Random Projections, robust biometrics, sparse representations |
| 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. |
| DOI | 10.1109/ICARCV.2010.5707955 |