A note on the estimation of viewer interest level using facial expression -Applying a framework for anomaly detection-

Abstract

This paper presents a method which estimates interest level by quantifying facial expression data captured from users while watching videos. In the proposed method, the framework for anomaly detection is newly applied to estimate interest level. Specifically ,by using a infrared depth sensor, our method obtains changes in facial expression as numerical features, which are obtained from users while they are watching the videos. Next, the probability distribution of the features is calculated to model changes in facial expression. Then, an anomaly score of changes in facial expression is obtained based on the probability distribution. Using the calculated anomaly score, interest level, which the change of facial expression represents, could be estimated. Finally, this paper shows the effectiveness of the proposed method through experimentation on real participants.