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Spatial Data: 3D Scalar Fields CS444 Recap: 2D contouring - PowerPoint PPT Presentation

Spatial Data: 3D Scalar Fields CS444 Recap: 2D contouring https://www.e-education.psu.edu/geog486/node/1873 Recap: 2D contouring Cases + - Case Polarity Rotation Total No Crossings x2 2 (x2 for Singlet x2 x4 8 polarity) x2


  1. Spatial Data: 3D Scalar Fields CS444

  2. Recap: 2D contouring https://www.e-education.psu.edu/geog486/node/1873

  3. Recap: 2D contouring Cases + - Case Polarity Rotation Total No Crossings x2 2 (x2 for Singlet x2 x4 8 polarity) x2 Double adjacent x2 (4) 4 x2 Double Opposite x1 (2) 2 16 = 2 4

  4. 3D Contouring

  5. 3D Contouring

  6. Splitting 3D space into simple shapes

  7. Cube into tetrahedra

  8. Cube into tetrahedra

  9. Cube into tetrahedra 1 tetrahedron,

  10. Cube into tetrahedra

  11. Cube into tetrahedra 2 tetrahedra

  12. Cube into tetrahedra 1 cube splits into 6 tetrahedra

  13. Cube into tetrahedra 1 cube splits into 6 tetrahedra… but also into 5 tetrahedra!

  14. Cube into tetrahedra

  15. Marching Tetrahedra 3 cases, “obvious”

  16. 3D Contouring

  17. 3D Contouring

  18. 3D Contouring `

  19. http://hint.fm/wind Spatial Data: Vector Fields

  20. https://www.youtube.com/watch?v=nuQyKGuXJOs Spatial Data: Vector Fields

  21. Experimental Flow Vis von Kármán vortex street, depending on Reynolds number

  22. http://envsci.rutgers.edu/~lintner/teaching.html Guadalupe Island

  23. Mathematics of Vector Fields v : R n → R n Function from vectors to vectors

  24. A simple vector field: the gradient https://www.youtube.com/watch?v=v0_LlyVquF8

  25. Vector fields can be more complicated v ( x, y ) = (cos( x + 2 y ) , sin( x − 2 y )) http://www.math.umd.edu/~petersd/241/html/ex27b.html

  26. Glyph Based Techniques

  27. Hedgehog Plot: Not Very Good

  28. Hedgehog Plot: Not Very Good From Laidlaw et al.’s “Comparing 2D Vector Field Visualization Methods: A User Study”, TVCG 2005

  29. Uniformly-placed arrows: Not Very Good Either

  30. Jittered Hedgehog Plot: Better

  31. Space-filling scaled glyphs

  32. Streamline-Guided Placement

  33. Streamline -Guided Placement

  34. Streamlines

  35. Streamlines

  36. Streamlines

  37. Curves everywhere tangent to the vector field

  38. Curves everywhere tangent to the vector field x 0 ( t ) = v x ( x ( t ) , y ( t )) y 0 ( t ) = v y ( x ( t ) , y ( t ))

  39. Visualization via streamlines • Pick a set of seed points • Integrate streamlines from those points • Which seed points?

  40. Uniform placement Turk and Banks, Image-Guided Streamline Placement SIGGRAPH 1996

  41. Density-optimized placement Turk and Banks, Image-Guided Streamline Placement SIGGRAPH 1996

  42. Density-optimized placement Turk and Banks, Image-Guided Streamline Placement SIGGRAPH 1996

  43. Image-Based Vector Field Visualization

  44. Line Integral Convolution http://www3.nd.edu/~cwang11/2dflowvis.html Cabral and Leedom, Imaging Vector Fields using Line Integral Convolution. SIGGRAPH 1993

  45. Line Integral Convolution Given a vector field compute streamlines convolve source of noise along streamlines Result

  46. Line Integral Convolution

  47. Advantages • “Perfect” space usage • Flow features are very apparent

  48. Downsides • No perception of velocity! • No perception of direction!

  49. Image-Based Flow Visualization • Adaptation of LIC for graphics cards • Extremely fast and simple to implement • Animation gives perception of velocity • (But requires knowledge of computer graphics, which we’re not assuming in this course)

  50. Image-Based Flow Visualization http://www.win.tue.nl/~vanwijk/ibfv/

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