Online nod detection in human-robot interaction

Abstract

Nodding is an important factor in human communication, providing a physical cue for socially communicative acts such as turn taking, backchanneling, and confirmation. In this article, we describe a vision-based online head nodding detector that works with monocular camera images. Using SVM regression, our system estimates the head pose based on facial landmarks. Subsequence dynamic time-warping is then used to compare head pose features against nod templates. In contrast to many other previous implementations, our system was evaluated with study participants who were not instructed to reply by nodding, and shows good results while maintaining a low false positive rate.