The Feasibility of RGB-D Gaze Intention Measurement in Children with Autism Using Azure Kinect

Gaze interpretation is a fundamental aspect of social communication, especially for children with autism spectrum disorder (ASD), who frequently encounter many difficulties in social interactions. Despite the considerable advances made in gaze tracking technologies, such as those based on RGB and RGB-D, the accurate measurement of gaze direction remains a significant scientific challenge. This paper proposes a novel approach utilizing the Azure Kinect to improve the measurement of gaze intention in children with ASD, providing accurate estimations of both gaze direction and head position. To evaluate the effectiveness of the proposed methodology, an experimental trial was conducted with eight participants of varying statures. The intersection of the estimated gaze with the target plane was also analyzed throughout 38-min sessions. The results demonstrated high accuracy, with a minimum angular error of 2.5° using pupil positions, 2.06° using head orientation, and average errors of 4.46° and 3.19°, respectively. This approach was tested on a dataset of children with ASD to track their gaze towards a clinician, as this information is essential for assessing the children's social intent and interactions with others, facilitating more precise clinical assessments for children with autism.