In this paper we address the problem that most face recognition approaches neglect that faces share strong visual similarities, which can be exploited when learning discriminative models. Hence, we propose to model face recognition as multi-task learning problem. This enables us to exploit both, shared common information and also individual characteristics of faces. In particular, we build on M...

Face recognition is one of the most important and rapidly advanced active research areas of computer science. In spite of the large number of developed algorithms, real-world performance of face recognition has been disappointing. This study enhances invariant recognition of human faces and analysis to improve face verification and identification performance using Active Appearance Model (AAM) ...

The development of large-scale facial identification systems that provide privacy protection the enrolled subjects represents an open challenge. In context protection, several template schemes have been proposed in past. However, these appear to be unsuitable for indexing (workload reduction) biometric systems. More precisely, they utilized performing exhaustive searches, thereby leading degrad...

Background: Internet of Medical Things (IOMT) has the potential to monitor health continuously and in real-time. One main issues that arise IOMT is how securely data can be transmitted clinical team. In this project, biometric Identity-based encryption was utilized using Fuzzy-IBE (Identity-based encryption) scheme uses face features clinicians create public key. Figure 1 shows testbed setup de...