A Two-stage Robust Statistical Method for Temporal Registration from Features of Various Type
Identifieur interne : 002118 ( Crin/Curation ); précédent : 002117; suivant : 002119A Two-stage Robust Statistical Method for Temporal Registration from Features of Various Type
Auteurs : Gilles Simon ; Marie-Odile BergerSource :
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Abstract
A model registration system capable of tracking an object, the model of which is known, in an image sequence is presented. It integrates tracking, pose determination and updating of the visible features. The heart of our system is the pose computation method, which handles various features (points, lines and free-form curves) in a very robust way and is able to give a correct estimate of the pose even when tracking errors occur. The reliability of the system is shown on an augmented reality project.
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en" wicri:score="159">A Two-stage Robust Statistical Method for Temporal Registration from Features of Various Type</title></titleStmt><publicationStmt><idno type="RBID">CRIN:simon98a</idno><date when="1998" year="1998">1998</date><idno type="wicri:Area/Crin/Corpus">002118</idno><idno type="wicri:Area/Crin/Curation">002118</idno><idno type="wicri:explorRef" wicri:stream="Crin" wicri:step="Curation">002118</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">A Two-stage Robust Statistical Method for Temporal Registration from Features of Various Type</title><author><name sortKey="Simon, Gilles" sort="Simon, Gilles" uniqKey="Simon G" first="Gilles" last="Simon">Gilles Simon</name></author><author><name sortKey="Berger, Marie Odile" sort="Berger, Marie Odile" uniqKey="Berger M" first="Marie-Odile" last="Berger">Marie-Odile Berger</name></author></analytic></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>augmented reality</term><term>registration</term><term>tracking</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en" wicri:score="1183">A model registration system capable of tracking an object, the model of which is known, in an image sequence is presented. It integrates tracking, pose determination and updating of the visible features. The heart of our system is the pose computation method, which handles various features (points, lines and free-form curves) in a very robust way and is able to give a correct estimate of the pose even when tracking errors occur. The reliability of the system is shown on an augmented reality project.</div></front></TEI><BibTex type="inproceedings"><ref>simon98a</ref><crinnumber>98-R-058</crinnumber><category>3</category><equipe>ISA</equipe><author><e>Simon, Gilles</e><e>Berger, Marie-Odile</e></author><title>A Two-stage Robust Statistical Method for Temporal Registration from Features of Various Type</title><booktitle>{Proceedings of 6th International Conference on Computer Vision, Bombay, India}</booktitle><year>1998</year><pages>261-266</pages><month>jan</month><url>http://www.loria.fr/publications/1998/98-R-058/98-R-058.ps</url><keywords><e>augmented reality</e><e>registration</e><e>tracking</e></keywords><abstract>A model registration system capable of tracking an object, the model of which is known, in an image sequence is presented. It integrates tracking, pose determination and updating of the visible features. The heart of our system is the pose computation method, which handles various features (points, lines and free-form curves) in a very robust way and is able to give a correct estimate of the pose even when tracking errors occur. The reliability of the system is shown on an augmented reality project.</abstract></BibTex></record>Pour manipuler ce document sous Unix (Dilib)
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