WPI - Computer Science Department, MS Thesis Presentation, Jiani Wang " Deep Multiple-Instance Learning for Stable Attribute Classification in Classroom Video" "
Deep Multiple-Instance Learning for Stable Attribute Classification in Classroom Video
WPI – Computer Science
Thursday, April 27, 2023
Time: 2:00 p.m.- 3:00 p.m.
Location: Unity Hall 320
Advisor: Prof. Jacob Richard Whitehill
Reader: Prof. Neil Heffernan
In this paper, we will explore how to classify multiple attributes of each person in a classroom video that are stable over short periods of time, such as their gender, role (student vs.~teacher), and skin tone. This can benefit the field of automatic classroom analysis so as to give teachers better feedback about their teaching and about possible biases they may have towards certain students.
We will tackle this problem using a deep Multiple-Instance Learning (MIL) method. We will also analyze the special aspects of classroom videos as compared to the kinds of data used in previous MIL research, and also explore strategies for how to deal with it.