Face authentication for e-Learning using time series information

One problem in e-Learning is that cheating by impersonation is easy. We examined variations in facial images taken with a webcam during e-Learning with the aim of detecting impersonation. In previous work, we proposed an authentication method based on updating a learner's facial images. This study examines weighted updating and the use of only the maximum similarity calculated instantaneously during the e-Learning session. The findings indicate that these proposed methods improve authentication accuracy.