<?xml version="1.0" encoding="ISO-8859-1"?>
<metadatalist>
	<metadata ReferenceType="Conference Proceedings">
		<site>sibgrapi.sid.inpe.br 802</site>
		<holdercode>{ibi 8JMKD3MGPEW34M/46T9EHH}</holdercode>
		<identifier>6qtX3pFwXQZG2LgkFdY/QMyVx</identifier>
		<repository>sid.inpe.br/sibgrapi@80/2007/07.18.03.11</repository>
		<lastupdate>2007:07.18.03.11.24 sid.inpe.br/banon/2001/03.30.15.38 administrator</lastupdate>
		<metadatarepository>sid.inpe.br/sibgrapi@80/2007/07.18.03.11.26</metadatarepository>
		<metadatalastupdate>2022:06.14.00.13.29 sid.inpe.br/banon/2001/03.30.15.38 administrator {D 2007}</metadatalastupdate>
		<doi>10.1109/SIBGRAPI.2007.13</doi>
		<citationkey>MaiaGomeSouz:2007:AuEyLo</citationkey>
		<title>Automatic Eye Localization in Color Images</title>
		<format>Printed, On-line.</format>
		<year>2007</year>
		<numberoffiles>1</numberoffiles>
		<size>410 KiB</size>
		<author>Maia, José Gilvan Rodrigues,</author>
		<author>Gomes, Fernando de Carvalho,</author>
		<author>Souza, Osvaldo de,</author>
		<affiliation>Departamento de Computação - Universidade Federal do Ceará (UFC)</affiliation>
		<affiliation>Departamento de Computação - Universidade Federal do Ceará (UFC)</affiliation>
		<affiliation>Depto. de Engenharia de Teleinformática – Universidade Federal do Ceará (UFC)</affiliation>
		<editor>Falcão, Alexandre Xavier,</editor>
		<editor>Lopes, Hélio Côrtes Vieira,</editor>
		<conferencename>Brazilian Symposium on Computer Graphics and Image Processing, 20 (SIBGRAPI)</conferencename>
		<conferencelocation>Belo Horizonte, MG, Brazil</conferencelocation>
		<date>7-10 Oct. 2007</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<transferableflag>1</transferableflag>
		<versiontype>finaldraft</versiontype>
		<keywords>Biometrics, eye detection, eye localization.</keywords>
		<abstract>In this paper, we present a new efficient method for accurate eye localization in color images. Our algorithm is based on robust feature filtering and explicit geometric clustering. This combination enhances localization speed and robustness by relying on geometric relationships between pixel clusters instead of other properties extracted from the image. Furthermore, its efficiency makes it well suited for implementation in low performance devices, such as cell phones and PDAs. Experiments were conducted with 1532 face images taken from a CCD camera under (real-life) varying illumination, pose and expression conditions. The proposed method presented a localization rate of 94.125% under such circumstances.</abstract>
		<language>en</language>
		<targetfile>maia-ColorImageEL.pdf</targetfile>
		<usergroup>gilvanmaia@gmail.com administrator</usergroup>
		<visibility>shown</visibility>
		<nexthigherunit>8JMKD3MGPEW34M/46SF8Q5</nexthigherunit>
		<nexthigherunit>8JMKD3MGPEW34M/4742MCS</nexthigherunit>
		<citingitemlist>sid.inpe.br/sibgrapi/2022/05.14.00.14 3</citingitemlist>
		<hostcollection>sid.inpe.br/banon/2001/03.30.15.38</hostcollection>
		<lasthostcollection>sid.inpe.br/banon/2001/03.30.15.38</lasthostcollection>
		<url>http://sibgrapi.sid.inpe.br/rep-/sid.inpe.br/sibgrapi@80/2007/07.18.03.11</url>
	</metadata>
</metadatalist>