Mirroring and recognizing emotions through facial expressions for a RoboKind platform

Abstract

The face embodies a large portion of the human emotionally expressive behaviour. Moreover, facial expressions are used to display emotional states and to manage interactions, being one of the most important channels of non-verbal communication. Although the process of recognition and displaying emotions is an easy task for the majority of humans, it is a very difficult task for individuals with Autism Spectrum Disorders (ASD). The present paper is a summary of a work developed under a Master Thesis on Industrial Electronics Engineering and Computers from the University of Minho, Portugal. The main goal of the work was the development and application of interactive and assistive technologies to support and promote new adaptive teaching/learning approaches for children with ASD. Therefore, it was proposed a system that uses the recent Intel RealSense 3D sensor to promote imitation and recognition of facial expressions, using a RoboKind Zeno R50 robot (ZECA) as a mediator in social activities. The system was first validated in the research laboratory and then tested in school environment with typically developing children and children with ASD.