Automatic face recognition system based on the SIFT features

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F15%3A43926858" target="_blank" >RIV/49777513:23520/15:43926858 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.compeleceng.2015.01.014" target="_blank" >http://dx.doi.org/10.1016/j.compeleceng.2015.01.014</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.compeleceng.2015.01.014" target="_blank" >10.1016/j.compeleceng.2015.01.014</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Automatic face recognition system based on the SIFT features

Popis výsledku v původním jazyce

The paper introduces an experimental fully automatic face recognition system which will be used to annotate photographs during insertion into the database. It processes photos of a great number of different individuals photographed in a totally uncontrolled environment. It uses our previously proposed SIFT based Kepenekci approach for face recognition. There is also proposed a new corpus creation algorithm. We show that this algorithm is beneficial in the preprocessing step of our system in order to create good quality face models. We further compare the performance of our SIFT based Kepenekci approach with the original Kepenekci method on the created corpus and our approach significantly outperforms the original one. The last contribution is proposition of two novel supervised confidence measure methods based on the posterior class probability and a multi-layer perceptron. We experimentally show that the proposed confidence measures are very efficient and thus suitable for our system.

Název v anglickém jazyce

Automatic face recognition system based on the SIFT features

Popis výsledku anglicky

The paper introduces an experimental fully automatic face recognition system which will be used to annotate photographs during insertion into the database. It processes photos of a great number of different individuals photographed in a totally uncontrolled environment. It uses our previously proposed SIFT based Kepenekci approach for face recognition. There is also proposed a new corpus creation algorithm. We show that this algorithm is beneficial in the preprocessing step of our system in order to create good quality face models. We further compare the performance of our SIFT based Kepenekci approach with the original Kepenekci method on the created corpus and our approach significantly outperforms the original one. The last contribution is proposition of two novel supervised confidence measure methods based on the posterior class probability and a multi-layer perceptron. We experimentally show that the proposed confidence measures are very efficient and thus suitable for our system.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

<a href="/cs/project/ED1.1.00%2F02.0090" target="_blank" >ED1.1.00/02.0090: NTIS - Nové technologie pro informační společnost</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název periodika

Computers &amp; Electrical Engineering

ISSN

0045-7906

e-ISSN

—

Svazek periodika

46

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

17

Strana od-do

256-272

Kód UT WoS článku

000367122800021

EID výsledku v databázi Scopus

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