Dual CNN-based Face Tracking Algorithm for an Automated Infant Monitoring System

Cheng Li, Genyu Song, A. Pourtaherian, P. H. N. de With

2021

Abstract

Face tracking is important for designing a surveillance system when facial features are used as main descriptors. In this paper, we propose an on-line updating face tracking method, which is not only suitable for specific tasks, such as infant monitoring, but also a generic human-machine interaction application where face recognition is required. The tracking method is based on combining the architecture of the GOTURN and YOLO tiny face detector, which enables the tracking model to be updated over time. Tracking of objects is realized by analyzing two neighboring frames through a deep neural network. On-line updating is achieved by comparing the tracking result and face detection obtained from the YOLO tiny face detector. The experimental results have shown that our proposed tracker achieves an AUC of 97.9% for precision plot and an AUC of 91.8% for success plot, which outperforms other state-of-the-art tracking methods when used in the infant monitoring application.

Paper Citation

in Harvard Style

Li C., Song G., Pourtaherian A. and N. de With P. (2021). Dual CNN-based Face Tracking Algorithm for an Automated Infant Monitoring System. 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 881-887. DOI: 10.5220/0010384308810887

in Bibtex Style

@conference{visapp21,
author={Cheng Li and Genyu Song and A. Pourtaherian and P. H. N. de With},
title={Dual CNN-based Face Tracking Algorithm for an Automated Infant Monitoring System},
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={881-887},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010384308810887},
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 - Dual CNN-based Face Tracking Algorithm for an Automated Infant Monitoring System
SN - 978-989-758-488-6
AU - Li C.
AU - Song G.
AU - Pourtaherian A.
AU - N. de With P.
PY - 2021
SP - 881
EP - 887
DO - 10.5220/0010384308810887
PB - SciTePress