Feature to Feature Matching for LBP Based Face Recognition
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F15%3A43927215" target="_blank" >RIV/49777513:23520/15:43927215 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-27101-9_28" target="_blank" >http://dx.doi.org/10.1007/978-3-319-27101-9_28</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-27101-9_28" target="_blank" >10.1007/978-3-319-27101-9_28</a>
Alternative languages
Result language
angličtina
Original language name
Feature to Feature Matching for LBP Based Face Recognition
Original language description
The paper presents a novel face recognition method called Local Binary Patterns with Feature to Feature Matching (LBP-FF). Contrary to other LBP approaches, we do not focus on the operator itself, however we would like to improve the matching procedure.The current LBP based approaches concatenate all feature vectors into one vector and then compare these large vectors. By contrast, our method compares the features separately. A sophisticated distance measure composed from two parts is used for face comparison. Chi square distance and histogram intersection metrics are utilized for vector distance computation. The proposed approach is evaluated on four face corpora: AT&T, FERET, AR and ČTK database. We experimentally show that our method significantlyoutperforms all compared state-of-the-art methods on all the databases.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
<a href="/en/project/LO1506" target="_blank" >LO1506: Sustainability support of the centre NTIS - New Technologies for the Information Society</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in Artificial Intelligence and Its Applications
ISBN
978-3-319-27100-2
ISSN
0302-9743
e-ISSN
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Number of pages
11
Pages from-to
371-381
Publisher name
Springer
Place of publication
Cham
Event location
Cuernavaca Morelos Mexico
Event date
Oct 25, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000367681400028