Child Engagement Estimation in Heterogeneous Child-Robot Interactions Using Spatiotemporal Visual Cues
Dafni Anagnostopoulou, Niki Efthymiou, Christina Papailiou, Petros Maragos
Abstract
Robots are increasingly introduced in various Child-Robot Interactions with educational, entertainment or even therapeutic goals. In order to achieve qualitative inter-actions, robots need to adjust their behavior according to children's response. A robot's ability to successfully estimate partner's engagement is of great importance towards this direction. In this research we propose a method to estimate the engagement level of children during heterogeneous and challenging child-robot interactions. Our method uses the spatiotemporal residual \mathrm{R}(2+1)\mathrm{D}\mathrm{R}(2+1)\mathrm{D} blocks to simultaneously leverage the rich RGB and temporal information, which is crucial for the engagement estimation. We present results on three different groups of data, including the PInSoRo open dataset, proving our method's robustness and improvement over previous works.
BibTeX
@inproceedings{iros2022_childengagemente,
title = {Child Engagement Estimation in Heterogeneous Child-Robot Interactions Using Spatiotemporal Visual Cues},
author = {Dafni Anagnostopoulou and Niki Efthymiou and Christina Papailiou and Petros Maragos},
booktitle = {IROS 2022},
year = {2022}
}