Jasmin Liao and Yu Sun, USA

Engaging online students is a challenge for many teachers. While I was a student, I saw teachers struggling to take attendance due to the number of students leaving their classes after attendance. Students would be held responsible for their work using facial recognition technology. To simplify the process of applying absences to students in each class, this paper proposes an application that would allow teachers to stay on top of their work. We applied our software to test “students” in the classroom and used various libraries/CSC styles to create a classroom that is easy for both the student and the teacher to read. Our designs are built upon OpenCV and PIL which are used as geometric classifiers to determine if the student is present. We tested several faces to see if the algorithm was suitable for the program. After conducting a qualitative evaluation of the approach, we’ve begun to implement registration, create new classrooms with different databases, and apply verification. With the addition of HTML code, we wereable to create a classroom that is safe, engaging, and easy to use.

Machine Learning, Artificial Intelligence, Python, JavaScript.