Simplifying flexible isosurfaces using local geometric measures

The contour tree, an abstraction of a scalar field that encodes the nesting relationships of isosurfaces, can be used to accelerate isosurface extraction, to identify important isovalues for volume-rendering transfer functions, and to guide exploratory visualization through a flexible isosurface interface. Many real-world data sets produce unmanageably large contour trees which require meaningful simplification. We define local geometric measures for individual contours, such as surface area and contained volume, and provide an algorithm to compute these measures in a contour tree. We then use these geometric measures to simplify the contour trees, suppressing minor topological features of the data. We combine this with a flexible isosurface interface to allow users to explore individual contours of a dataset interactively.

[1]  Valerio Pascucci On the topology of the level sets of a scalar field , 2001, CCCG.

[2]  William E. Lorensen,et al.  Marching cubes: a high resolution 3D surface construction algorithm , 1996 .

[3]  Yi-Jen Chiang,et al.  Progressive Simplification of Tetrahedral Meshes Preserving All Isosurface Topologies , 2003, Comput. Graph. Forum.

[4]  Yuriko Takeshima,et al.  Topological volume skeletonization using adaptive tetrahedralization , 2004, Geometric Modeling and Processing, 2004. Proceedings.

[5]  Herbert Edelsbrunner,et al.  Simulation of simplicity: a technique to cope with degenerate cases in geometric algorithms , 1988, SCG '88.

[6]  Jesse Freeman,et al.  in Morse theory, , 1999 .

[7]  Valerio Pascucci,et al.  Efficient computation of the topology of level sets , 2002, IEEE Visualization, 2002. VIS 2002..

[8]  Jack Snoeyink,et al.  Path Seeds and Flexible Isosurfaces - Using Topology for Exploratory Visualization , 2003, VisSym.

[9]  Jarek Rossignac,et al.  The Safari interface for visualizing time-dependent volume data using iso-surfaces and contour spectra , 2003, Comput. Geom..

[10]  Roberto Scopigno,et al.  A modified look-up table for implicit disambiguation of Marching Cubes , 1994, The Visual Computer.

[11]  Jack Snoeyink,et al.  Computing contour trees in all dimensions , 2000, SODA '00.

[12]  Herbert Edelsbrunner,et al.  Topological Persistence and Simplification , 2000, Proceedings 41st Annual Symposium on Foundations of Computer Science.

[13]  Yukio Matsumoto An Introduction to Morse Theory , 2001 .

[14]  Mikhail N. Vyalyi,et al.  Construction of contour trees in 3D in O(n log n) steps , 1998, SCG '98.

[15]  松本 幸夫 An introduction to Morse theory , 2002 .

[16]  Herbert Edelsbrunner,et al.  Hierarchical Morse—Smale Complexes for Piecewise Linear 2-Manifolds , 2003, Discret. Comput. Geom..

[17]  B. Hamann,et al.  A multi-resolution data structure for two-dimensional Morse-Smale functions , 2003, IEEE Visualization, 2003. VIS 2003..

[18]  M. V. D. Panne,et al.  Topological manipulation of isosurfaces , 2004 .

[19]  William E. Lorensen,et al.  Marching cubes: A high resolution 3D surface construction algorithm , 1987, SIGGRAPH.

[20]  Taku Komura,et al.  Topology matching for fully automatic similarity estimation of 3D shapes , 2001, SIGGRAPH.

[21]  Valerio Pascucci,et al.  The contour spectrum , 1997, Proceedings. Visualization '97 (Cat. No. 97CB36155).

[22]  Valerio Pascucci,et al.  Contour trees and small seed sets for isosurface traversal , 1997, SCG '97.

[23]  Yuriko Takeshima,et al.  Topological volume skeletonization and its application to transfer function design , 2004, Graph. Model..

[24]  Jack Snoeyink,et al.  Simplicial subdivisions and sampling artifacts , 2001, Proceedings Visualization, 2001. VIS '01..

[25]  Ken Brodlie,et al.  Recent Advances in Volume Visualization , 2001, Comput. Graph. Forum.

[26]  Jon Louis Bentley,et al.  Decomposable Searching Problems , 1979, Inf. Process. Lett..