Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.jvcir.2010.07.004
DC FieldValue
dc.titleDesign and implementation of geo-tagged video search framework
dc.contributor.authorKim, S.H.
dc.contributor.authorArslan Ay, S.
dc.contributor.authorZimmermann, R.
dc.date.accessioned2013-07-04T07:48:56Z
dc.date.available2013-07-04T07:48:56Z
dc.date.issued2010
dc.identifier.citationKim, S.H., Arslan Ay, S., Zimmermann, R. (2010). Design and implementation of geo-tagged video search framework. Journal of Visual Communication and Image Representation 21 (8) : 773-786. ScholarBank@NUS Repository. https://doi.org/10.1016/j.jvcir.2010.07.004
dc.identifier.issn10473203
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/39760
dc.description.abstractUser generated video content is experiencing significant growth which is expected to continue and further accelerate. As an example, users are currently uploading 20 h of video per minute to YouTube. Making such video archives effectively searchable is one of the most critical challenges of multimedia management. Current search techniques that utilize signal-level content extraction from video struggle to scale. Here we present a framework based on the complementary idea of acquiring sensor streams automatically in conjunction with video content. Of special interest are geographic properties of mobile videos. The meta-data from sensors can be used to model the coverage area of scenes as spatial objects such that videos can effectively, and on a large scale, be organized, indexed and searched based on their field-of-views. We present an overall framework that is augmented with our design and implementation ideas to illustrate the feasibility of this concept of managing geo-tagged video. © 2010 Elsevier Inc. All rights reserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/j.jvcir.2010.07.004
dc.sourceScopus
dc.subjectGeo-tagging
dc.subjectGPS
dc.subjectMeta-data
dc.subjectMobile video
dc.subjectScalability
dc.subjectSensor
dc.subjectVideo ranking
dc.subjectVideo search
dc.typeArticle
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1016/j.jvcir.2010.07.004
dc.description.sourcetitleJournal of Visual Communication and Image Representation
dc.description.volume21
dc.description.issue8
dc.description.page773-786
dc.description.codenJVCRE
dc.identifier.isiut000283827500002
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