Prediction of Learner’s gazing region for educational support robot Tabot Egg

Abstract

In educational support systems using robots, gaze information is considered to play an im- portant role. There have been many reports on eye gaze for children with regular development or with developmental disorder in learning support systems using robots. On the other hand, there are few find- ings for children with “mild developmental disorder”. Tabot Egg is an educational robot that aims to support the education of children with mild developmental disorder. Until now, Tabot Egg has not been equipped to collect and analyze gaze information. Therefore, we have implemented a function in Tabot Egg to analyze eye gaze data. In this study, we installed an image sensor on Tabot Egg and collected gaze information from test subjects to predict gazing regions. The experiment in this paper set up two classes of the gazing regions: a robot region and a non-robot region. The classes were predicted by inputting the gaze information obtained from the image sensor. As an experimental result, the mean accuracy achieves 75%. Based on the result here, we also investigated the possibility of a multi-class classification problem, i.e., high-resolutional gazing-region prediction.