Novel Matching Methods for Automatic Face Recognition Using SIFT

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F12%3A43916019" target="_blank" >RIV/49777513:23520/12:43916019 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1007/978-3-642-33409-2_27" target="_blank" >http://dx.doi.org/10.1007/978-3-642-33409-2_27</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-642-33409-2_27" target="_blank" >10.1007/978-3-642-33409-2_27</a>

Result language

angličtina

Original language name

Novel Matching Methods for Automatic Face Recognition Using SIFT

Original language description

The object of interest of this paper is Automatic Face Recognition (AFR). The goal is to propose and implement new AFR approaches that perform well also with few training examples. Our approaches extend the successful method based on the Scale InvariantFeature Transform (SIFT) proposed by Aly. We propose and evaluate two methods: the Lenc-Kral matching and the SIFT based Kepenekci approach. Our approaches are evaluated on two face data-sets: the ORL database and the Czech News Agency (CTK) corpus. We experimentally show that the proposed approaches significantly outperform the baseline Aly method on both corpora.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

JD - Use of computers, robotics and its application

OECD FORD branch

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Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2012

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

AIAI 2012. Vol. I.

ISBN

978-3-642-33408-5

ISSN

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e-ISSN

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Number of pages

10

Pages from-to

254-263

Publisher name

Springer

Place of publication

Heidelberg

Event location

Halkidiki

Event date

Sep 27, 2012

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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