CHILDATTEND: A Neural Network based Approach to Assess Child Attendance in Social Project Activities

João Estrela, Wladmir Brandão

2021

Abstract

Social project sponsors demand transparency in the application of donated resources. A challenge for nongovernmental organizations that support children is to provide proof of children’s participation in social project activities for sponsors. Additionally, the proof of participation by roll call or paper reports is much less convincing than automatic attendance checking by image analysis. Despite recent advances in face recognition, there is still room for improvement when algorithms are fed with only one instance of a person’s face, since that person can significantly change over the years, especially children. Furthermore, face recognition algorithms still struggle in special cases, e.g., when there are many people in different poses and the photos are taken under variant lighting conditions. In this article we propose a neural network based approach that exploits face detection, face recognition and image alignment algorithms to identify children in activity group photos, i.e., images with many people performing activities, often on the move. Experiments show that the proposed approach is fast and identifies children in activity group photos with more than 90% accuracy.

Paper Citation

in Harvard Style

Estrela J. and Brandão W. (2021). CHILDATTEND: A Neural Network based Approach to Assess Child Attendance in Social Project Activities. In Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-509-8, pages 602-609. DOI: 10.5220/0010400406020609

in Bibtex Style

@conference{iceis21,
author={João Estrela and Wladmir Brandão},
title={CHILDATTEND: A Neural Network based Approach to Assess Child Attendance in Social Project Activities},
booktitle={Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2021},
pages={602-609},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010400406020609},
isbn={978-989-758-509-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - CHILDATTEND: A Neural Network based Approach to Assess Child Attendance in Social Project Activities
SN - 978-989-758-509-8
AU - Estrela J.
AU - Brandão W.
PY - 2021
SP - 602
EP - 609
DO - 10.5220/0010400406020609