Although online education is a paramount pillar of formal, non-formal and informal learning, institutions may still be reluctant to wager for a fully online educational model. As such, there is still a reliance on face-to-face assessment, since online alternatives do not have the deserved expected social recognition and reliability. Thus, the creation of an e-assessment system that will be able to provide effective proof of student identity, authorship within the integration of selected technologies in current learning activities in a scalable and cost efficient manner would be very advantageous. The TeSLA project provides to educational institutions, an adaptive trust e-assessment system for assuring e-assessment processes in online and blended environments. It will support both continuous and final assessment to improve the trust level across students, teachers and institutions.
This is a large Program Grant aimed at advancing the science of machine face perception and face matching technology in order to enable automatic retrieval, recognition, and verification of faces and facial behaviours in images and videos recorded in the wild (e.g. CCTV camera recordings). The coordinator of the project is Prof. Josef Kittler of Surrey University and the team at Imperial College is responsible for tracking of faces in the wild, for learning and tracking of dynamic facial biomarkers (i.e. facial behaviometrics), and data-driven learning and tracking of soft biometrics.
Team: Maja Pantic, Stefanos Zafeiriou, TK Kim, Krystian Mikolajczyk