A Systematic Literature Review on the Accuracy of Face Recognition Algorithms

Authors

DOI:

https://doi.org/10.4108/eetiot.v8i30.2346

Keywords:

Accuracy, Convolutional Neural Networks, Facial Recognition, Viola-Jones Algorithm

Abstract

Real-time facial recognition systems have been increasingly used, making it relevant to address the accuracy of these systems given the credibility and trust they must offer. Therefore, this article seeks to identify the algorithms currently used by facial recognition systems through a Systematic Literature Review that considers recent scientific articles, published between 2018 and 2021. From the initial collection of ninety-three articles, a subset of thirteen was selected after applying the inclusion and exclusion procedures. One of the outstanding results of this research corresponds to the use of algorithms based on Artificial Neural Networks (ANN) considered in 21% of the solutions, highlighting the use of Convolutional Neural Network (CNN). Another relevant result is the identification of the use of the Viola-Jones algorithm, present in 19% of the solutions. In addition, from this research, two specific facial recognition solutions associated with access control were found considering the principles of the Internet of Things, one being applied to access control to environments and the other applied to smart cities.

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Published

12-09-2022

How to Cite

[1]
M. A. Lazarini, R. Rossi, and K. Hirama, “A Systematic Literature Review on the Accuracy of Face Recognition Algorithms ”, EAI Endorsed Trans IoT, vol. 8, no. 30, p. e5, Sep. 2022.

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Vol. 8 No. 30 (2022): EAI Endorsed Transactions on Internet of Things

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Research article

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