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A weighted regional voting based ensemble of multiple classifiers for face recognition.
Digital Document
Abstract |
Abstract
Face recognition is heavily studied for its wide range of application in areas such as information security, law enforcement, surveillance of the environment, entertainment, smart cards, etc. Competing techniques have been proposed in computer vision conferences and journals, no algorithm has emerged as superior in all cases over the last decade. In this work, we developed a framework which can embed all available algorithms and achieve better results in all cases over the algorithms that we have embedded, without great sacrifice in time complexity. We build on the success of a recently raised concept - Regional Voting. The new system adds weights to different regions of the human face. Different methods of cooperation among algorithms are also proposed. Extensive experiments, carried out on benchmark face databases, show the proposed system's joint contribution from multiple algorithms is faster and more accurate than Regional Voting in every case. --P. ix. |
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Persons |
Persons
Author (aut): Cheng, Jing
Thesis advisor (ths): Chen, Liang
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Degree Name
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Department
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DOI |
DOI
https://doi.org/10.24124/2012/bpgub864
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Collection(s)
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Degree granting institution (dgg): University of Northern British Columbia
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Library of Congress Classification |
Library of Congress Classification
TA1650 .C44 2011
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Extent |
Extent
Number of pages in document: 54
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Physical Form
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Handle
Handle placeholder
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ISBN |
ISBN
978-0-494-87531-5
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Use and Reproduction |
Use and Reproduction
Copyright retained by the author.
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Rights Statement |
Rights Statement
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unbc_16200.pdf2.47 MB
20143-Extracted Text.txt86.28 KB
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Language |
English
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Name |
A weighted regional voting based ensemble of multiple classifiers for face recognition.
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application/pdf
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2584853
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