Efficient Multi-task based Facial Landmark and Gesture Detection in Monocular Images

Jon Goenetxea, Luis Unzueta, Unai Elordi, Oihana Otaegui, Fadi Dornaika, Fadi Dornaika

2021

Abstract

The communication between persons includes several channels to exchange information between individuals. The non-verbal communication contains valuable information about the context of the conversation and it is a key element to understand the entire interaction. The facial expressions are a representative example of this kind of non-verbal communication and a valuable element to improve human-machine interaction interfaces. Using images captured by a monocular camera, automatic facial analysis systems can extract facial expressions to improve human-machine interactions. However, there are several technical factors to consider, including possible computational limitations (e.g. autonomous robots), or data throughput (e.g. centralized computation server). Considering the possible limitations, this work presents an efficient method to detect a set of 68 facial feature points and a set of key facial gestures at the same time. The output of this method includes valuable information to understand the context of communication and improve the response of automatic human-machine interaction systems.

Paper Citation

in Harvard Style

Goenetxea J., Unzueta L., Elordi U., Otaegui O. and Dornaika F. (2021). Efficient Multi-task based Facial Landmark and Gesture Detection in Monocular Images. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP; ISBN 978-989-758-488-6, SciTePress, pages 680-687. DOI: 10.5220/0010373006800687

in Bibtex Style

@conference{visapp21,
author={Jon Goenetxea and Luis Unzueta and Unai Elordi and Oihana Otaegui and Fadi Dornaika},
title={Efficient Multi-task based Facial Landmark and Gesture Detection in Monocular Images},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP},
year={2021},
pages={680-687},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010373006800687},
isbn={978-989-758-488-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP
TI - Efficient Multi-task based Facial Landmark and Gesture Detection in Monocular Images
SN - 978-989-758-488-6
AU - Goenetxea J.
AU - Unzueta L.
AU - Elordi U.
AU - Otaegui O.
AU - Dornaika F.
PY - 2021
SP - 680
EP - 687
DO - 10.5220/0010373006800687
PB - SciTePress