Face-Based Attention Recognition Model for Children with Autism Spectrum Disorder.

ABSTRACT: Attention recognition plays a vital role in providing learning support for children with autism spectrum disorders (ASD). The unobtrusiveness of face-tracking techniques makes it possible to build automatic systems to detect and classify attentional behaviors. However, constructing such systems is a challenging task due to the complexity of attentional behavior in ASD. This paper proposes a face-based attention recognition model using two methods. The first is based on geometric feature transformation using a support vector machine (SVM) classifier, and the second is based on the transformation of time-domain spatial features to 2D spatial images using a convolutional neural network (CNN) approach. We conducted an experimental study on different attentional tasks for 46 children (ASD n<

SUBMITTER: Banire B 

PROVIDER: S-EPMC8982782 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature