Age estimation is a valuable forensic tool for criminal investigators since it helps to identify minors or possible offenders in Child Sexual Exploitation Materials (CSEM). Nowadays, Deep Learning methods are considered state-of-the-art for general age estimation. However, they have low performance in predicting the age of minors and older adults because of the few examples of these age groups in the existing datasets. Moreover, facial occlusion is used by offenders in certain CSEM, trying to hide the identity of the victims, which may also affect the performance of age estimators. In this work, we assess the performance of six deep-learning-based age estimators on non-occluded and occluded facial images. We selected FG-Net and APPA-REAL datasets to evaluate the models under non-occluded conditions. To assess the models under occluded conditions, we created synthetically occluded versions of the non-occluded datasets by drawing eye and mouth black masks to simulate the conditions observed in some CSEM images. Experimental results showed that the evaluated age estimators are affected more by eye occlusion than by mouth occlusion. Also, facial occlusion affects more the accuracy of the age estimation of minors and the elderly compared to other age groups. We expect that this study could become an initial benchmark for age estimation under non-occluded and occluded conditions, especially for forensic applications like victim profiling on CSEM where age estimation is essential.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.