Comparisons of Facial Recognition Algorithms Through a Case Study Application
Dublin Core
Title
Comparisons of Facial Recognition Algorithms Through a Case Study Application
Subject
Facial Recognition Algorithms
OpenFace
Mobile Facial recognitions
Description
Abstract— Computer visions and their applications have become important in contemporary life. Hence, researches on facial and object recognition have become increasingly important both from academicians and practitioners. Smart gadgets such as smartphones are nowadays capable of high processing power, memory capacity, along with high resolutions camera. Furthermore, the connectivity bandwidth and the speed of the interaction have significantly impacted the popularity of mobile object recognition applications. These developments in addition to computer vision’s algorithms advancement have transferred object’s recognitions from desktop environments to the mobile world. The aim of this paper to reveal the efficiency and accuracy of the existing open-source facial recognition algorithms in real-life settings. We use the following popular open-source algorithms for efficiency evaluations: Eigenfaces, Fisherfaces, Local Binary Pattern Histogram, the deep convolutional neural network algorithm, and OpenFace. The evaluations of the test cases indicate that among the compared facial recognition algorithms the OpenFace algorithm has the highest accuracy to identify faces. The findings of this study help the practitioner on their decision of the algorithm selections and the academician on how to improve the accuracy of the current algorithms even further.
Creator
Dirin, Amir
Delbiaggio, Nicolas
Kauttonen, Janne
Source
International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 14 (2020); pp. 121-133
1865-7923
Publisher
International Association of Online Engineering (IAOE), Vienna, Austria
Date
2020-08-28
Rights
Copyright (c) 2020 Amir Dirin, Nicolas Delbiaggio, Janne Kauttonen
Relation
Format
application/pdf
Language
eng
Type
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
Identifier
Citation
Amir Dirin, Nicolas Delbiaggio and Janne Kauttonen, Comparisons of Facial Recognition Algorithms Through a Case Study Application, International Association of Online Engineering (IAOE), Vienna, Austria, 2020, accessed November 5, 2024, https://igi.indrastra.com/items/show/1747