The 2013 face recognition evaluation in mobile environment

Automatic face recognition in unconstrained environments is a challenging task. To test current trends in face recognition algorithms, we organized an evaluation on face recognition in mobile environment. This paper presents the results of 8 different participants using two verification metrics. Most submitted algorithms rely on one or more of three types of features: local binary patterns, Gabor wavelet responses including Gabor phases, and color information. The best results are obtained from UNILJ-ALP, which fused several image representations and feature types, and UC-HU, which learns optimal features with a convolutional neural network. Additionally, we assess the usability of the algorithms in mobile devices with limited resources. © 2013 IEEE

Biometric Template Protection Using Universal Background Models: An Application to Online Signature

Data security and privacy are crucial issues to be addressed for assuring a successful deployment of biometrics-based recognition systems in real life applications. In this paper, a template protection scheme exploiting the properties of universal background models, eigen-user spaces, and the fuzzy commitment cryptographic protocol is presented. A detailed discussion on the security and information leakage of the proposed template protection system is given. The effectiveness of the proposed approach is investigated with application to online signature recognition. The given experimental results, evaluated on the public MCYT signature database, show that the proposed system can guarantee competitive recognition accuracy while providing protection to the employed biometric data

Eigen-model Projections for Protected On-line Signature Recognition

The protection of the templates stored in a biometric recognition system represents an issue of paramount importance for the security and privacy of the enrolled users, and directly affects the successful deployment of the system itself. In this paper we propose a protected on-line signature recognition system where the properties of Universal Background Models are exploited to provide a small dimensionality and a limited intra-class variability signature representation. The reported experimental results show that the employed signature representation and protection scheme allow to reach high recognition accuracy while providing protection to the considered biometric data