Feature tracking of 3D scalar datasets in the 'visit' environment

Abstract

OF THE THESIS Feature Tracking of 3D Scalar Datasets in the ‘VisIt’ Environment by Rohini M Pangrikar Thesis Director: Professor Deborah Silver Visualization of 3D scientific time varying datasets is a challenging task due to the large amount of data to be processed. Such datasets can contain evolving patterns, visualization of which can give an intuitive interpretation of a dataset under study. The Vizlab at Rutgers has pioneered in the development of feature tracking of 3D scalar datasets by isolating features or region of interest and tracking them over subsequent time steps by using spatial matching. Once these features are extracted and tracked, their evolutionary information can be used for iso-surface visualization by color coding each feature such that evolving patterns are easy to follow. This thesis presents the development of Feature Tracking of 3D scalar datasets in VisIt, a free interactive parallel visualization and graphical analysis tool for viewing scientific data. The implementation is divided into two modules. The first module, implemented as ‘FeatureTrack’ operator plugin, performs feature extraction, quantification and stores iso-surface information for each time step, then tracks features over subsequent timesteps. The second module, implemented in conjunction with the ‘polyfile’ reader plugin, ‘TrackPoly’ operator plugin and ‘PolyDataPlot’ plot plugin, performs visualization. Separation of visualization from feature tracking enables ‘selective enhanced visualization’ so only features of interest are selected and tracked over time.