3D Human Sensing, Action and Emotion Recognition in Robot Assisted Therapy of Children with Autism
Abstract
We introduce new, fine-grained action and emotion recognition tasks defined on non-staged videos, recorded during robot-assisted therapy sessions of children with autism. The tasks present several challenges: a large dataset with long videos, a large number of highly variable actions, children that are only partially visible, have different ages and may show unpredictable behaviour, as well as non-standard camera viewpoints. We investigate how state-of-the-art 3d human pose reconstruction methods perform on the newly introduced tasks and propose extensions to adapt them to deal with these challenges. We also analyze multiple approaches in action and emotion recognition from 3d human pose data, establish several baselines, and discuss results and their implications in the context of child-robot interaction.
Cite
Text
Marinoiu et al. "3D Human Sensing, Action and Emotion Recognition in Robot Assisted Therapy of Children with Autism." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018. doi:10.1109/CVPR.2018.00230Markdown
[Marinoiu et al. "3D Human Sensing, Action and Emotion Recognition in Robot Assisted Therapy of Children with Autism." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018.](https://mlanthology.org/cvpr/2018/marinoiu2018cvpr-3d/) doi:10.1109/CVPR.2018.00230BibTeX
@inproceedings{marinoiu2018cvpr-3d,
title = {{3D Human Sensing, Action and Emotion Recognition in Robot Assisted Therapy of Children with Autism}},
author = {Marinoiu, Elisabeta and Zanfir, Mihai and Olaru, Vlad and Sminchisescu, Cristian},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2018},
doi = {10.1109/CVPR.2018.00230},
url = {https://mlanthology.org/cvpr/2018/marinoiu2018cvpr-3d/}
}