A system for automated attendance through face verification, as well as finding interest levels of a student in e-learning

Principal Investigator: Dr. Aurobinda Routray

Co-researchers: Shubhobrata Bhattacharya

• Algorithm to classify the mark the attendance of a student through face verification

• Estimation of attention index through face image sequences using deep learning

• Estimation of expression index through face image sequences using deep learning

• Estimation of head pose index through face image sequences using deep learning

• Attendance in most large classrooms is conducted manually, resulting in considerate amount of wastage of time

• Chance of impersonation is more in cases of manual attendance

• There are no standard systems to provide the interest level of the student in a course

The student needs to register for the course with Name, Frontal face images, and other details

Upon login-in, the student needs to verify for his face against the credentials to mark attendance as well as verify impersonation

There is provision to play a video lecture, either online or offline recorded

With the start of a lecture, the recording of facial images of the student begins

The recording of facial images is analysed framewise

Each facial frame is check with a classifier concerning expression, eye state and head pose

Finally the indices are computed