A Survey on Comparison of Face Recognition Algorithms
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Date
2014
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Open Access Color
Green Open Access
No
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Publicly Funded
No
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Impulse
Top 10%
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Top 10%
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Top 10%
Abstract
The identification of a face from a video or image source is a study of computer vision know as face detection or recognition. Face detection and recognition becomes popular in recent years by the development of computing power. In this study we will present performance aspect of algorithms Eigenfaces, Fisherfaces, and Local Binary Pattern Histograms in different development platforms: Arm and Intel processors. © 2016 Elsevier B.V., All rights reserved.
Description
Chevron; EMC2; et al.; itkz; MIKRO Information Handling and Distribution FZE; Thomson Reuters
Ozdil, Ahmet/0000-0002-6651-1968;
Ozdil, Ahmet/0000-0002-6651-1968;
ORCID
Keywords
Eigenfaces, Embedded, Face Recognition, Fisherface, Lbph, Algorithms, Computer Vision, Microprocessor Chips, Development Platform, Eigenfaces, Embedded, Face Detection and Recognition, Face Recognition Algorithms, Fisherface, Lbph, Local Binary Patterns, Face Recognition
Fields of Science
0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology
Citation
WoS Q
N/A
Scopus Q
N/A
OpenCitations Citation Count
18
Source
-- 8th IEEE International Conference on Application of Information and Communication Technologies, AICT 2014 -- Astana -- 112596
Volume
Issue
Start Page
249
End Page
251
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CrossRef : 3
Scopus : 29
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Mendeley Readers : 70
SCOPUS™ Citations
31
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1
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2
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