Automatically Detected Feature Positions 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%2F14%3A43922830" target="_blank" >RIV/49777513:23520/14:43922830 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-662-44654-6_24" target="_blank" >http://dx.doi.org/10.1007/978-3-662-44654-6_24</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-662-44654-6_24" target="_blank" >10.1007/978-3-662-44654-6_24</a>
Alternative languages
Result language
angličtina
Original language name
Automatically Detected Feature Positions for LBP Based Face Recognition
Original language description
This paper presents a novel approach for automatic face recognition based on the Local Binary Patterns (LBP). One drawback of the current LBP based methods is that the feature positions are fixed and thus do not reflect the properties of the particular images. We propose to solve this issue by a method that automatically detects feature positions in the image. These key-points are determined using the Gabor wavelet transform and k-means clustering algorithm. The proposed method is evaluated on two corpora: AT&T Database of Faces and our Czech News Agency (ČTK) dataset containing uncontrolled face images. The recognition rate on the first dataset is 99.5% which represents 2.5% improvement compared to the original LBP method. The best recognition rate obtained on the ČTK corpus is 59.1% whereas the original LBP method reaches only 38.1%.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Result continuities
Project
<a href="/en/project/ED1.1.00%2F02.0090" target="_blank" >ED1.1.00/02.0090: NTIS - New Technologies for Information Society</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Artificial Intelligence Applications and Innovations
ISBN
978-3-662-44653-9
ISSN
1868-4238
e-ISSN
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Number of pages
10
Pages from-to
246-255
Publisher name
Springer
Place of publication
Heidelberg
Event location
Rhodos
Event date
Sep 19, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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