The quickhull algorithm for convex hulls
ACM Transactions on Mathematical Software (TOMS)
Image-guided streamline placement
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
A flow-guided streamline seeding strategy
Proceedings of the conference on Visualization '00
Smooth approximation and rendering of large scattered data sets
Proceedings of the conference on Visualization '01
Adaptive smooth scattered-data approximation for large-scale terrain visualization
VISSYM '03 Proceedings of the symposium on Data visualisation 2003
Strategies for interactive exploration of 3D flow using evenly-spaced illuminated streamlines
SCCG '03 Proceedings of the 19th spring conference on Computer graphics
VIS '04 Proceedings of the conference on Visualization '04
An Advanced Evenly-Spaced Streamline Placement Algorithm
IEEE Transactions on Visualization and Computer Graphics
Image-Based Streamline Generation and Rendering
IEEE Transactions on Visualization and Computer Graphics
Priority streamlines: a context-based visualization of flow fields
EUROVIS'07 Proceedings of the 9th Joint Eurographics / IEEE VGTC conference on Visualization
Difference of inflow and outflow based 3D streamline placement
Proceedings of the 3rd International Symposium on Visual Information Communication
Automatic Stream Surface Seeding: A Feature Centered Approach
Computer Graphics Forum
Surface curvature line clustering for polyp detection in CT colonography
EG VCBM'08 Proceedings of the First Eurographics conference on Visual Computing for Biomedicine
Visual reconstructability as a quality metric for flow visualization
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
Effective texture models for three dimensional flow visualization
Proceedings of the 28th Spring Conference on Computer Graphics
Opacity optimization for 3D line fields
ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
Multiresolution streamline placement based on control grids
Integrated Computer-Aided Engineering
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Most streamline generation algorithms either provide a particular density of streamlines across the domain or explicitly detect features, such as critical points, and follow customized rules to emphasize those features. However, the former generally includes many redundant streamlines, and the latter requires Boolean decisions on which points are features (and may thus suffer from robustness problems for real-world data). We take a new approach to adaptive streamline placement for steady vector fields in 2D and 3D. We define a metric for local similarity among streamlines and use this metric to grow streamlines from a dense set of candidate seed points. The metric considers not only Euclidean distance, but also a simple statistical measure of shape and directional similarity. Without explicit feature detection, our method produces streamlines that naturally accentuate regions of geometric interest. In conjunction with this method, we also propose a quantitative error metric for evaluating a streamline representation based on how well it preserves the information from the original vector field. This error metric reconstructs a vector field from points on the streamline representation and computes a difference of the reconstruction from the original vector field.