Eye Tracking for Autism Disorder Analysis using Image Processing

Abstract

Analyzing eyes performance is essential for effective functioning of human. Therefore, following their motion could help doctors to make quick and accurate diagnoses for disorders like Autism, schizophrenia, or attention deficit hyperactivity disorder. Recently, several studies investigated autism disorder diagnosis and treatment. Meanwhile, various algorithms have been provided for eye tracking. In this paper, it is intended to identify diagnosis parameters of autism disorder using eye tracking concept. The eye tracking algorithm that has been used in this research is simple and sufficient accurate to appropriate function on videos with varying quality. The direct analysis of gaze and study of the interactions of its features are employed a useful method for diagnosis of autism. For this purpose, two separate groups of ordinary children and children with autism are considered. By tracking their eyes while watching television and performing the necessary analyses then their eye movements are compared and discussed. To identify pupils is face detection Viola Jones algorithm is implemented.