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 22, 2024, https://igi.indrastra.com/items/show/1747

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