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Assessing the Influencing Factors on the Accuracy of Underage Facial Age Estimation
Date Issued
2020-06-19
Date Available
2023-09-20T14:29:11Z
Abstract
Swift response to the detection of endangered minors is an ongoing concern for law enforcement. Many child-focused investigations hinge on digital evidence discovery and analysis. Automated age estimation techniques are needed to aid in these investigations to expedite this evidence discovery process, and decrease investigator exposure to traumatic material. Automated techniques also show promise in decreasing the overflowing backlog of evidence obtained from increasing numbers of devices and online services. A lack of sufficient training data combined with natural human variance has been long hindering accurate automated age estimation - especially for underage subjects. This paper presented a comprehensive evaluation of the performance of two cloud age estimation services (Amazon Web Service's Rekognition service and Microsoft Azure's Face API) against a dataset of over 21,800 underage subjects. The objective of this work is to evaluate the influence that certain human biometric factors, facial expressions, and image quality (i.e. blur, noise, exposure and resolution) have on the outcome of automated age estimation services. A thorough evaluation allows us to identify the most influential factors to be overcome in future age estimation systems.
Type of Material
Conference Publication
Publisher
IEEE
Copyright (Published Version)
2020 IEEE
Web versions
Language
English
Status of Item
Peer reviewed
Journal
International Conference on Cyber Security and Protection of Digital Services, Cyber Security 2020
Conference Details
The IEEE International Conference on Cyber Security and Protection of Digital Services (Cyber Security 2020), Dublin, Ireland, 15-19 June 2020
ISBN
9781728164281
This item is made available under a Creative Commons License
File(s)
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Name
Cyber_Security_2020__Age_Estimation (5).pdf
Size
746.43 KB
Format
Adobe PDF
Checksum (MD5)
319cf3e301906d3ea8a57104aa27cc3e
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