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The State of the Art in Flow Visualisation: Feature Extraction and Tracking
Author(s) -
Post Frits H.,
Vrolijk Benjamin,
Hauser Helwig,
Laramee Robert S.,
Doleisch Helmut
Publication year - 2003
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/j.1467-8659.2003.00723.x
Subject(s) - computer science , visualization , feature extraction , scientific visualization , cluster analysis , computer graphics , feature (linguistics) , data mining , field (mathematics) , data visualization , interactive visualization , grid , artificial intelligence , computer graphics (images) , pattern recognition (psychology) , mathematics , linguistics , philosophy , geometry , pure mathematics
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