Genetic Algorithm for Weight Optimization in Descriptor Based Face Recognition Methods
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F16%3A43929341" target="_blank" >RIV/49777513:23520/16:43929341 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.5220/0005704403300336" target="_blank" >http://dx.doi.org/10.5220/0005704403300336</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5220/0005704403300336" target="_blank" >10.5220/0005704403300336</a>
Alternative languages
Result language
angličtina
Original language name
Genetic Algorithm for Weight Optimization in Descriptor Based Face Recognition Methods
Original language description
This paper presents a novel algorithm for weight optimization in descriptor based face recognition methods. We aim at the local texture features. Common concept in such methods is creating histograms of the operator values in rectangular image regions and concatenating them into one large vector called histogram sequence (HS). Usually the facial regions are given equal weight which does not correspond with the reality. We propose a novel method that optimizes the weights of the regions. The optimization method is based on a genetic algorithm (GA). We test the method together with the LBP and POEM descriptors. We evaluate our algorithms on two real-world corpora: Unconstrained facial images (UFI) database and FaceScrub database. The results show that the weighted methods outperform the non-weighted ones. The best achieved scores are 68.93% on the UFI database and 57.81% on the FaceScrub database.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
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
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 8th International Conference on Agents and Artificial Intelligence
ISBN
978-989-758-172-4
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
330-336
Publisher name
SciTePress
Place of publication
Setúbal
Event location
Řím
Event date
Feb 24, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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