Children with Autism Spectrum Disorder (ASD) are known to have difficulty in producing and perceiving emotional facial expressions. Their expressions are often perceived as atypical by adult observers. This paper focuses on data driven ways to analyze and quantify atypicality in facial expressions of children with ASD. Our objective is to uncover those characteristics of facial gestures that induce the sense of perceived atypicality in observers. Using a carefully collected motion capture database, facial expressions of children with and without ASD are compared within six basic emotion categories employing methods from information theory, time-series modeling and statistical analysis. Our experiments show that children with ASD exhibit lower complexity in facial dynamics, with the eye regions contributing more than other facial regions towards the differences between children with and without ASD. Our study also notes that children with ASD exhibit lower left-right facial symmetry, and more uniform motion intensity across facial regions.
For example, Guha et al. REF used motion capture data to quantify atypicality difference in facial expressions of children with and without ASC.
On quantifying facial expression-related atypicality of children with Autism Spectrum Disorder
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Computer Science Medicine