Using Facial Recognition Technology in Smart Attendance Application
The following research was done at Tokyo Academics in a team of 3. The research was published with the Turkish Online Journal for Educational Technology and was presented at Harvard University and at the Shibaura Institute of Technology. I have included the abstract, but you can find the paper in the link →HERE← on page 878.
We propose to use a facial recognition technology in a smart attendance application in order to make the attendance taking process more efficient. The conventional method, such as manual roll call, is inefficient and time consuming. However, with the application of facial recognition technology, the attendance taking process becomes automated and unobtrusive, thereby making it a smarter alternative to traditional methods. In this paper, we introduce an open source attendance taking program using OpenFace for the facial recognition module. We use a machine learning approach to build a classification model to identify a person’s name from the unique facial features of an individual subject. In an experiment, we have verified the accuracy of the facial recognition module at 96.2% given our test using 50 subjects. The result is tolerable for a school/organization with a small number of users. This could be implemented within a classroom to assist administration through automating roll call.
1 year (2017 - 2018)
Language and Tools:
Written in Python, Openface