Improving Age Estimation in Minors and Young Adults with Occluded Faces to Fight Against Child Sexual Exploitation

Deisy Chaves, Deisy Chaves, Eduardo Fidalgo, Eduardo Fidalgo, Enrique Alegre, Enrique Alegre, Francisco Jáñez-Martino, Francisco Jáñez-Martino, Rubel Biswas, Rubel Biswas

2020

Abstract

Accurate and fast age estimation is crucial in systems for detecting possible victims in Child Sexual Exploitation Materials. Age estimation obtains state of the art results with deep learning. However, these models tend to perform poorly in minors and young adults, because they are trained with unbalanced data and few examples. Furthermore, some Child Sexual Exploitation images present eye occlusion to hide the identity of the victims, which may also affect the performance of age estimators. In this work, we evaluate the performance of Soft Stagewise Regression Network (SSR-Net), a compact size age estimator model, with non-occluded and occluded face images. We propose an approach to improve the age estimation in minors and young adults by using both types of facial images to create SSR-Net models. The proposed strategy builds robust age estimators that improve SSR-Net pre-trained models on IMBD and MORPH datasets, and a Deep EXpectation model, reducing the Mean Absolute Error (MAE) from 7.26, 6.81 and 6.5 respectively, to 4.07 with our proposal.

Paper Citation

in Harvard Style

Chaves D., Fidalgo E., Alegre E., Jáñez-Martino F. and Biswas R. (2020). Improving Age Estimation in Minors and Young Adults with Occluded Faces to Fight Against Child Sexual Exploitation. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP; ISBN 978-989-758-402-2, SciTePress, pages 721-729. DOI: 10.5220/0008945907210729

in Bibtex Style

@conference{visapp20,
author={Deisy Chaves and Eduardo Fidalgo and Enrique Alegre and Francisco Jáñez-Martino and Rubel Biswas},
title={Improving Age Estimation in Minors and Young Adults with Occluded Faces to Fight Against Child Sexual Exploitation},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP},
year={2020},
pages={721-729},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008945907210729},
isbn={978-989-758-402-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP
TI - Improving Age Estimation in Minors and Young Adults with Occluded Faces to Fight Against Child Sexual Exploitation
SN - 978-989-758-402-2
AU - Chaves D.
AU - Fidalgo E.
AU - Alegre E.
AU - Jáñez-Martino F.
AU - Biswas R.
PY - 2020
SP - 721
EP - 729
DO - 10.5220/0008945907210729
PB - SciTePress