Visual System for Student Attendance Monitoring with Non-standard Situation Detection
Abstract— In this paper we propose a visual system for
monitoring of student attendance in seminars and lectures.Basic idea is to estimate the number of people in the room
using face detection algorithms and subsequently utilize face
recognition algorithms to determine the actual identification
of persons (students). Presented approach may be used for
multiple purposes. Principal and primary purpose is to
monitor attendance, which is possible thanks to university
database. When implemented, system is expected to evaluate
the attendance automatically or if necessary using
collaborative authentication. Non-standard or anomaly
detection is another feature that is to be provided by system,
subject to tracking are hands, eyes and movement.
Proposed solution is expected to improve and facilitate
attendance monitoring of students at seminars and lectures.
Further it may be used for anomaly prevention (e.g.
cheating) and in specific cases for security or legal matters.
