| dc.description.abstract | In recent years, facial recognition technology has made more and more progress in real world applications and systems. Primarily, security and privacy are among the top concerns
regarding the applicability of face recognition. With the ability to identify each individual from
unique facial structures and features, face recognition has the potential to become a reliable
security method. However, the performance and accuracy of face recognition algorithms are
challenging problems that prevent people from using them. This thesis aims to create a
simulated banking web application, and apply face recognition to enhance security when
authenticating and transferring. Specifically, Dlib[19] is used as the face detector, Facenet512
[1] is the face recognition model in the application. Face expression analysis with
HyperExtended LightFace [28] is also employed to prevent or reduce the risk of using face
photos instead of real faces. Moreover, to choose the most suitable face recognition model for
the application, experiments are performed to evaluate performance between state-of-the-art
face recognition models. At the end, Facenet512 is the chosen one thanks to its excellent
precision, high accuracies and fast execution time | en_US |
