Classification of gaze pattern using face direction for mother-infant interactions during shared book reading

Abstract

Joint attention is important for the language development of infant and often observed in interactions during shared book reading. In the observation of the joint attention, though the gaze is an important element, the analysis of the gaze has been carried out by the manual coding from the video image by experimenter until now, and it requires large labor. In order to automate this coding, we have developed a system to identify joint attention of mother and infant based on the face direction detected using machine learning from the images captured by a webcam. In this paper, we discuss gaze patterns using the system under development from the results of coding by the experimenter. And, the effect of deviation of gaze direction and face direction on the classification of gaze pattern was examined.