Issue No. 08 - Aug. (2012 vol. 18)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2011.155
Ching-Kuang Shene , Dept. of Comput. Sci., Michigan Technol. Univ., Townsend, MA, USA
Chaoli Wang , Dept. of Comput. Sci., Michigan Technol. Univ., Townsend, MA, USA
Hongfeng Yu , Combustion Res. Facility, Sandia Nat. Labs., Livermore, CA, USA
J. H. Chen , Combustion Res. Facility, Sandia Nat. Labs., Livermore, CA, USA
Effective 3D streamline placement and visualization play an essential role in many science and engineering disciplines. The main challenge for effective streamline visualization lies in seed placement, i.e., where to drop seeds and how many seeds should be placed. Seeding too many or too few streamlines may not reveal flow features and patterns either because it easily leads to visual clutter in rendering or it conveys little information about the flow field. Not only does the number of streamlines placed matter, their spatial relationships also play a key role in understanding the flow field. Therefore, effective flow visualization requires the streamlines to be placed in the right place and in the right amount. This paper introduces hierarchical streamline bundles, a novel approach to simplifying and visualizing 3D flow fields defined on regular grids. By placing seeds and generating streamlines according to flow saliency, we produce a set of streamlines that captures important flow features near critical points without enforcing the dense seeding condition. We group spatially neighboring and geometrically similar streamlines to construct a hierarchy from which we extract streamline bundles at different levels of detail. Streamline bundles highlight multiscale flow features and patterns through clustered yet not cluttered display. This selective visualization strategy effectively reduces visual clutter while accentuating visual foci, and therefore is able to convey the desired insight into the flow data.
rendering (computer graphics), critical points, flow visualisation, pattern clustering, pattern formation, critical points, hierarchical streamline bundles, 3D streamline placement, 3D streamline visualization, seed placement, rendering, spatial relationships, 3D flow field visualization, spatially neighboring streamlines, geometrically similar streamlines, streamline bundle extraction, multiscale flow features, multiscale flow patterns, visual clutter reduction, visual foci accentuation, flow data, flow saliency, streamline seeding, Three dimensional displays, Streaming media, Feature extraction, Data visualization, Clustering algorithms, Visualization, Diffusion tensor imaging, flow visualization., Streamline bundles, flow saliency, seed placement, hierarchical clustering, level-of-detail
Ching-Kuang Shene, Chaoli Wang, Hongfeng Yu and J. H. Chen, "Hierarchical Streamline Bundles," in IEEE Transactions on Visualization & Computer Graphics, vol. 18, no. , pp. 1353-1367, 2012.