%0 Journal Article %1 CGF:CGF723 %A Post, Frits H. %A Vrolijk, Benjamin %A Hauser, Helwig %A Laramee, Robert S. %A Doleisch, Helmut %D 2003 %I Blackwell Publishing, Inc %J Computer Graphics Forum %K flow graphics motion_analysis tracking visualization %N 4 %P 775--792 %R 10.1111/j.1467-8659.2003.00723.x %T The State of the Art in Flow Visualisation: Feature Extraction and Tracking %U http://dx.doi.org/10.1111/j.1467-8659.2003.00723.x %V 22 %X Flow 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—applications

@article{CGF:CGF723, abstract = {Flow 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—applications}, added-at = {2014-09-29T09:48:57.000+0200}, author = {Post, Frits H. and Vrolijk, Benjamin and Hauser, Helwig and Laramee, Robert S. and Doleisch, Helmut}, biburl = {https://www.bibsonomy.org/bibtex/28aef0980b216f357ed22e8bf02197da4/alex_ruff}, description = {The State of the Art in Flow Visualisation: Feature Extraction and Tracking - Post - 2004 - Computer Graphics Forum - Wiley Online Library}, doi = {10.1111/j.1467-8659.2003.00723.x}, interhash = {efa43fe9f8f43d76463eaeb1dc250b9a}, intrahash = {8aef0980b216f357ed22e8bf02197da4}, issn = {1467-8659}, journal = {Computer Graphics Forum}, keywords = {flow graphics motion_analysis tracking visualization}, number = 4, pages = {775--792}, publisher = {Blackwell Publishing, Inc}, timestamp = {2014-09-29T09:48:57.000+0200}, title = {The State of the Art in Flow Visualisation: Feature Extraction and Tracking}, url = {http://dx.doi.org/10.1111/j.1467-8659.2003.00723.x}, volume = 22, year = 2003 }