Open AccessClass Monitoring System Tools MTCNN and Haarcascade Classifier
Author(s) -
Aditya Vikram Bhattacharya,
M. Rajesh Khanna,
Akshay Tripathi,
S Murugaveni
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i3.12.17609
Subject(s) - attendance , timestamp , computer science , class (philosophy) , python (programming language) , classifier (uml) , scope (computer science) , multimedia , world wide web , artificial intelligence , real time computing , operating system , programming language , economics , economic growth
The project aims towards the assistance of teachers at the time of taking attendance. The system solely focuses on face detection and recognition. The tools used to device the system are API’s offered by Python 3.6, Open CV(for detection) and a few cognitive tools provided by Azure.The basic idea behind the project is face recognition linked to a database backend. The information of the student attending the class is stored here. The entire attendance is associated with two types of time stamps incorporated at the server end. The time stamp helps to keep a track of the hour conducted and the time for which number of people attended the class. Exceptions in the time stamp would be incorporated in order to cater for the students leaving the class or trying to bunk the class. In case of further exceptionsin the time stamp will be scope of further development of the system. All queries or conditions of the students will be answered by the system on communication with the admin. If the admin finds that the system was at fault then it can always be fixed by the admin for smooth functioning of the class monitoring system.