@conference {72,
	title = {Automated facial affect analysis for one-on-one tutoring applications},
	booktitle = {2011 IEEE International Conference on Automatic Face Gesture Recognition and Workshops (FG 2011)},
	year = {2011},
	month = {03/2011},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Santa Barbara, CA},
	abstract = {<p><span style="color: rgb(68, 68, 68); font-family: {\textquoteright}Lucida Grande{\textquoteright}, Verdana, sans-serif; font-size: 14px; background-color: rgba(0, 0, 0, 0.0470588);">In this paper, we explore the use of computer vision techniques to analyze students{\textquoteright} moods during one-on-one teaching interactions. The eventual goal is to create automated tutoring systems that are sensitive to the student{\textquoteright}s mood and affective state. We find that the problem of accurately determining a child{\textquoteright}s mood from a single video frame is surprisingly difficult, even for humans. However when the system is allowed to make decisions based on information from 10 to 30 seconds of video, excellent performance may be obtained.</span></p>
},
	keywords = {automated facial affect analysis, automated tutoring system, behavioural sciences computing, computer vision technique, Context, decision making, education, Emotion recognition, face recognition, Human, human computer interaction, Labeling, Machine Learning, Mood, n Histograms, one-on-one tutoring application, s Intelligent tutoring systems, student mood analysis},
	isbn = {978-1-4244-9140-7},
	author = {Butko, N. and Theocharous, G. and Philipose, M. and Movellan, J.}
}
