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dc.contributor.authorPost, Frits H.en_US
dc.contributor.authorVrolijk, Benjaminen_US
dc.contributor.authorHauser, Helwigen_US
dc.contributor.authorLaramee, Robert S.en_US
dc.contributor.authorDoleisch, Helmuten_US
dc.date.accessioned2014-07-29T13:41:51Z
dc.date.available2014-07-29T13:41:51Z
dc.date.issued2003en_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttp://dx.doi.org/10.1111/j.1467-8659.2003.00723.xen_US
dc.description.abstractFlow visualisation is an attractive topic in data visualisation, offering great challenges for research. Very large data sets must be processed, consisting of multivariate data at large numbers of grid points, often arranged in many time steps. Recently, the steadily increasing performance of computers again has become a driving force for new advances in flow visualisation, especially in techniques based on texturing, feature extraction, vector field clustering, and topology extraction.In this article we present the state of the art in feature-based flow visualisation techniques. We will present numerous feature extraction techniques, categorised according to the type of feature. Next, feature tracking and event detection algorithms are discussed, for studying the evolution of features in time-dependent data sets. Finally, various visualisation techniques are demonstrated.ACM CSS: I.3.8 Computer Graphics-applicationsen_US
dc.publisherBlackwell Publishing, Inc and Eurographics Associationen_US
dc.titleThe State of the Art in Flow Visualisation: Feature Extraction and Trackingen_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume22en_US
dc.description.number4en_US
dc.identifier.doi10.1111/j.1467-8659.2003.00723.xen_US
dc.description.documenttypestar


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