Mixing Synthetic and Video Images of an Outdoor Urban Environment
Identifieur interne : 003232 ( Hal/Curation ); précédent : 003231; suivant : 003233Mixing Synthetic and Video Images of an Outdoor Urban Environment
Auteurs : Marie-Odile Berger [France] ; Brigitte Wrobel-Dautcourt [France] ; Sylvain Petitjean [France] ; Gilles Simon [France]Source :
- Machine Vision and Applications [ 0932-8092 ] ; 1999.
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Abstract
Mixing video and computer-generated images is a new and promising area of research for enhancing reality. It can be used in all the situations when a complete simulation would not be easy to implement. Past work on the subject has relied for a large part on human intervention at key moments of the composition. In this paper, we show that if enough geometric information about the environment are available, then efficient tools developed in the computer vision literature can be used to build a highly automated augmented reality loop. We focus on outdoor urban environments and present an application for the visual assessment of a new lighting project of the bridges of Paris.
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xml:lang="en">Mixing video and computer-generated images is a new and promising area of research for enhancing reality. It can be used in all the situations when a complete simulation would not be easy to implement. Past work on the subject has relied for a large part on human intervention at key moments of the composition. In this paper, we show that if enough geometric information about the environment are available, then efficient tools developed in the computer vision literature can be used to build a highly automated augmented reality loop. We focus on outdoor urban environments and present an application for the visual assessment of a new lighting project of the bridges of Paris.</div></front></TEI><hal api="V3"><titleStmt><title xml:lang="en">Mixing Synthetic and Video Images of an Outdoor Urban Environment</title><author role="aut"><persName><forename type="first">Marie-Odile</forename><surname>Berger</surname></persName><email>berger@loria.fr</email><idno type="halauthor">129828</idno><orgName ref="#struct-300009"></orgName><affiliation ref="#struct-2350"></affiliation></author><author role="aut"><persName><forename type="first">Brigitte</forename><surname>Wrobel-Dautcourt</surname></persName><email></email><idno type="halauthor">129955</idno><affiliation ref="#struct-2350"></affiliation></author><author role="aut"><persName><forename type="first">Sylvain</forename><surname>Petitjean</surname></persName><email></email><idno type="halauthor">60838</idno><affiliation ref="#struct-2350"></affiliation></author><author role="aut"><persName><forename type="first">Gilles</forename><surname>Simon</surname></persName><email></email><idno type="halauthor">100927</idno><affiliation ref="#struct-2350"></affiliation></author><editor role="depositor"><persName><forename>Publications</forename><surname>Loria</surname></persName><email>publications@loria.fr</email></editor></titleStmt><editionStmt><edition n="v1" type="current"><date type="whenSubmitted">2006-09-26 08:38:49</date><date type="whenModified">2016-05-19 01:09:28</date><date type="whenReleased">2006-09-28 15:22:44</date><date type="whenProduced">1999</date></edition><respStmt><resp>contributor</resp><name key="108626"><persName><forename>Publications</forename><surname>Loria</surname></persName><email>publications@loria.fr</email></name></respStmt></editionStmt><publicationStmt><distributor>CCSD</distributor><idno type="halId">inria-00098820</idno><idno type="halUri">https://hal.inria.fr/inria-00098820</idno><idno type="halBibtex">berger:inria-00098820</idno><idno type="halRefHtml">Machine Vision and Applications, Springer Verlag, 1999, 11 (3), pp.145-159</idno><idno type="halRef">Machine Vision and Applications, Springer Verlag, 1999, 11 (3), pp.145-159</idno></publicationStmt><seriesStmt><idno type="stamp" n="INRIA">INRIA - Institut National de Recherche en Informatique et en Automatique</idno><idno type="stamp" n="CNRS">CNRS - Centre national de la recherche scientifique</idno><idno type="stamp" n="INPL">Institut National Polytechnique de Lorraine</idno><idno type="stamp" n="LORIA2">Publications du LORIA</idno><idno type="stamp" n="LORIA">LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications</idno><idno type="stamp" n="INRIA-NANCY-GRAND-EST">INRIA Nancy - Grand Est</idno><idno type="stamp" n="UNIV-LORRAINE">Université de Lorraine</idno><idno type="stamp" n="INRIA-LORRAINE">INRIA Nancy - Grand Est</idno><idno type="stamp" n="LABO-LORIA-SET" p="LORIA">LABO-LORIA-SET</idno></seriesStmt><notesStmt><note type="commentary">Article dans revue scientifique avec comité de lecture.</note><note type="audience" n="1">Not set</note><note type="popular" n="0">No</note><note type="peer" n="1">Yes</note></notesStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Mixing Synthetic and Video Images of an Outdoor Urban Environment</title><author role="aut"><persName><forename type="first">Marie-Odile</forename><surname>Berger</surname></persName><email>berger@loria.fr</email><idno type="halAuthorId">129828</idno><orgName ref="#struct-300009"></orgName><affiliation ref="#struct-2350"></affiliation></author><author role="aut"><persName><forename type="first">Brigitte</forename><surname>Wrobel-Dautcourt</surname></persName><idno type="halAuthorId">129955</idno><affiliation ref="#struct-2350"></affiliation></author><author role="aut"><persName><forename type="first">Sylvain</forename><surname>Petitjean</surname></persName><idno type="halAuthorId">60838</idno><affiliation ref="#struct-2350"></affiliation></author><author role="aut"><persName><forename type="first">Gilles</forename><surname>Simon</surname></persName><idno type="halAuthorId">100927</idno><affiliation ref="#struct-2350"></affiliation></author></analytic><monogr><idno type="localRef">99-R-015 || berger99a</idno><idno type="halJournalId" status="VALID">16814</idno><idno type="issn">0932-8092</idno><idno type="eissn">1432-1769</idno><title level="j">Machine Vision and Applications</title><imprint><publisher>Springer Verlag</publisher><biblScope unit="volume">11</biblScope><biblScope unit="issue">3</biblScope><biblScope unit="pp">145-159</biblScope><date type="datePub">1999</date></imprint></monogr></biblStruct></sourceDesc><profileDesc><langUsage><language ident="en">English</language></langUsage><textClass><keywords scheme="author"><term xml:lang="fr">réalité augmentée</term><term xml:lang="fr">tracking</term><term xml:lang="fr">augmented reality</term><term xml:lang="fr">viewpoint computation</term><term xml:lang="fr">point de vue</term><term xml:lang="fr">suivi</term></keywords><classCode scheme="halDomain" n="info.info-oh">Computer Science [cs]/Other [cs.OH]</classCode><classCode scheme="halTypology" n="ART">Journal articles</classCode></textClass><abstract xml:lang="en">Mixing video and computer-generated images is a new and promising area of research for enhancing reality. It can be used in all the situations when a complete simulation would not be easy to implement. Past work on the subject has relied for a large part on human intervention at key moments of the composition. In this paper, we show that if enough geometric information about the environment are available, then efficient tools developed in the computer vision literature can be used to build a highly automated augmented reality loop. We focus on outdoor urban environments and present an application for the visual assessment of a new lighting project of the bridges of Paris.</abstract></profileDesc></hal></record>Pour manipuler ce document sous Unix (Dilib)
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