Journal of Mathematical Imaging and Vision
A new Voronoi-based surface reconstruction algorithm
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
Zoom-invariant vision of figural shape: the mathematics of cores
Computer Vision and Image Understanding
Edge Detection and Ridge Detection with Automatic Scale Selection
International Journal of Computer Vision
Proceedings of the conference on Visualization '01
The Ball-Pivoting Algorithm for Surface Reconstruction
IEEE Transactions on Visualization and Computer Graphics
Provably good sampling and meshing of surfaces
Graphical Models - Solid modeling theory and applications
High-Quality Extraction of Isosurfaces from Regular and Irregular Grids
IEEE Transactions on Visualization and Computer Graphics
Triangulating point set surfaces with bounded error
SGP '05 Proceedings of the third Eurographics symposium on Geometry processing
Efficient Visualization of Lagrangian Coherent Structures by Filtered AMR Ridge Extraction
IEEE Transactions on Visualization and Computer Graphics
Invariant Crease Lines for Topological and Structural Analysis of Tensor Fields
IEEE Transactions on Visualization and Computer Graphics
Sampling and Visualizing Creases with Scale-Space Particles
IEEE Transactions on Visualization and Computer Graphics
Crease Surfaces: From Theory to Extraction and Application to Diffusion Tensor MRI
IEEE Transactions on Visualization and Computer Graphics
Polygonizing extremal surfaces with manifold guarantees
Proceedings of the 14th ACM Symposium on Solid and Physical Modeling
Anisotropy creases delineate white matter structure in diffusion tensor MRI
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Galilean invariant extraction and iconic representation of vortex core lines
EUROVIS'05 Proceedings of the Seventh Joint Eurographics / IEEE VGTC conference on Visualization
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We present a novel algorithm for the efficient extraction and visualization of high-quality ridge and valley surfaces from numerical datasets. Despite their rapidly increasing popularity in visualization, these so-called crease surfaces remain challenging to compute owing to their strongly nonlinear and non-orientable nature, and their complex boundaries. In this context, existing meshing techniques require an extremely dense sampling that is computationally prohibitive. Our proposed solution intertwines sampling and meshing steps to yield an accurate approximation of the underlying surfaces while ensuring the geometric quality of the resulting mesh. Using the computation power of the GPU, we propose a fast, parallel method for sampling. Additionally, we present a new front propagation meshing strategy that leverages CPU multiprocessing. Results are shown for synthetic, medical and fluid dynamics datasets.