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How Feature Tracking Works
Here you can find brief information about Feature Tracking. However a more broad and accurate information can be found on Vizlab main web site.
Visualizing and analyzing 3D time-varying datasets (4D datasets scalar/vector) is very difficult because of the immense amount of data to be processed and understood. These datasets contain many evolving amorphous regions, and it is difficult to observe patterns and visually follow regions of interest. An essential part of the scientific process is to identify, quantify and track important regions and structures (objects of interest). This is true for almost all disciplines since the crux of understanding the original simulation, experiment or observation is the study of the evolution of the ``objects'' present. Some well known examples include tracking the progression of a storm, the motion and change of the ``ozone hole'', or the movement of vortices shed by the meandering Gulf stream. What is needed is visualization, quantification and querying techniques to help filter and reduce the data to a form more conducive to analysis. This is complementary to the standard visualization and helps explain in more mathematical and quantitative detail what is being seen.
Feature Track project aimed to solve this problem. Our Feature Track algorithm works on other platforms as well, however the most recent version of the algorithm runs on VisIt platform. VisIt is an opensource visualization and analysis software.
- is an opensource software that runs on various operating systems,
- supports parallel processing,
- supports various types of datasets,
- provides various visualization and analysing tools for different type of data.
More information on VisIt software can be found at here.
FeatureTracking adds more value to VisIt at this point where the scientists need to look at their time varying 3D datasets.
Our feature tracking algorithm runs on VisIt and :
- tracks objects in time and assignes the same color to the same objects in consecutive time frames, instead of assigning random colors to each feature in time,
- works as a plugin on VisIt environment, thus supports the datasets that VisIt supports automatically,
- instead of visualizing all the features in the dataset, it allows users to focus on specific features that they would like to pay attention on, thus it reduces the "visual clutter",
- By reducing the visual clutter, it allows scientists to carry their datasets in a reduced form.
Briefly, our feature tracking algorithm helps scientists to analyse their simulations and their dataset.
How the algorithm works:
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Scientists are building their simulations based on models in order to describe a phenomenon or a system in a better way. During their simulations, lots of data are being generated and there is a need to visualize this dataset in a meaningful way. These datasets includes some certain "features". Features are the objects that the scientists are interested in their simulations. Feature tracking project, fundamentally, formed of following steps:
Detailed information on how our algorithm works can be found on main VizLab website as well as on the publications [1] [2] and [3]. |
[1] D. Silver and X. Wang, Volume Tracking. IEEE Visualization '96 Conference Proceeding. October 1996.
[2] D. Silver, Object Oriented Visualization. IEEE Computer Graphics and Applications, Volume 15, Number 3, May 1995.
[3] R. Samtaney, D. Silver, N. Zabusky, and J. Cao, Visualizing Features and Tracking Their Evolution, IEEE Computer, Volume 27, Number 7, pp. 20-27, July 1994.