Recently, different smart glasses solutions have been proposed on the market. The rapid development of this wearable technology has led to several research projects related to applications of smart glasses in healthcare. In this paper we propose a general architecture of the system enabling data integration for the recognized person. In the proposed system smart glasses integrates data obtained for the recognized patient from health care information systems, from devices connected to the patient and from the patient himself. The data integration is possible, if proper patient recognition procedure is used. Therefore, we evaluated three identification methods based on face recognition and using the recognition of graphical markers (i.e. QR-codes and proposed color-based codes). The results show that it is possible to obtain reliable and fast recognition results during the video acquisition by the smart glasses camera.
Biometric identification systems, i.e. the systems that are able to recognize humans by analyzing their physiological or behavioral characteristics, have gained a lot of interest in recent years. They can be used to raise the security level in certain institutions or can be treated as a convenient replacement for PINs and passwords for regular users. Automatic face recognition is one of the most popular biometric technologies, widely used even by many low-end consumer devices such as netbooks. However, even the most accurate face identification algorithm would be useless if it could be cheated by presenting a photograph of a person instead of the real face. Therefore, the proper liveness measurement is extremely important. In this paper we present a method that differentiates between video sequences showing real persons and their photographs. First we calculate the optical flow of the face region using the Farnebäck algorithm. Then we convert the motion information into images and perform the initial data selection. Finally, we apply the Support Vector Machine to distinguish between real faces and photographs. The experimental results confirm that the proposed approach could be successfully applied in practice.
Electronic documents constitute specific units of information, and protecting them against unauthorized access is a challenging task. This is because a password protected document may be stolen from its host computer or intercepted while on transfer and exposed to unlimited offline attacks. The key issue is, therefore, making document passwords hard to crack. We propose to augment a common text password authentication interface to encrypted documents with a biometric facial identity verification providing highly personalized security mechanism based on pseudo-identities. In consequence the encrypted document can be unlocked with the legitimate user’s face, while for everyone else stays encrypted with a hard to crack text password. This paper makes two contributions: (1) The proposed scheme enables password autofill without referring to any external service, which significantly limits the possibilities of an attack by adversaries when opening, reading and editing the protected document, (2) By the adoption of biometric verification techniques enabling fine-tuning of false acceptance and false rejection rates, it provides for responsible adaptation to users.
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