Visualizing Gaze Direction to Support Video Coding of Social Attention

By | July 2, 2018

Keita Higuchi, Soichiro Matsuda, Rie Kamikubo, Takuya Enomoto, Yusuke Sugano, Jun’ichi Yamamoto, and Yoichi Sato, “Visualizing Gaze Direction to Support Video Coding of Social Attention for Children with Autism Spectrum Disorder”, Proceedings of IUI 2018

This paper presents a novel interface to support video coding of social attention in the assessment of children with autism spectrum disorder. Video-based evaluations of social attention during therapeutic activities allow observers to find target behaviors while handling the ambiguity of attention. Despite the recent advances in computer vision-based gaze estimation methods, fully automatic recognition of social attention under diverse environments is still challenging. The goal of this work is to investigate an approach that uses automatic video analysis in a supportive manner for guiding human judgment. The proposed interface displays visualization of gaze estimation results on videos and provides GUI support to allow users to facilitate agreement between observers by defining social attention labels on the video timeline. Through user studies and expert reviews, we show how the interface helps observers perform video coding of social attention and how human judgment compensates for technical limitations of the automatic gaze analysis.