Fast Computation of Generalized Voronoi Diagrams Using Graphics Hardware Kenneth E. Hoff III, Tim Culver, John Keyser, M

1. Fast Computation of Generalized Voronoi Diagrams Using Graphics Hardware Kenneth E. Hoff III, Tim Culver, John Keyser, Ming Lin, and Dinesh Manocha University of North Carolina at Chapel Hill SIGGRAPH ‘99

2. What is a Voronoi Diagram? Given a collection of geometric primitives, it is a subdivision of space into cells such that all points in a cell are closer to one primitive than to any other Voronoi Site Voronoi Region

3. Generalized • Higher-order site geometry • Varying distance metrics Ordinary • Point sites • Nearest Euclidean distance Higher-orderSites 2.0 0.5 Weighted Distances

4. Why Should We Compute Them? It is a fundamental concept Descartes Astronomy 1644 “Heavens” Dirichlet Math 1850 Dirichlet tesselation Voronoi Math 1908 Voronoi diagram Boldyrev Geology 1909 area of influence polygons Thiessen Meteorology 1911 Theissen polygons Niggli Crystallography 1927 domains of action Wigner & Seitz Physics 1933 Wigner-Seitz regions Frank & Casper Physics 1958 atom domains Brown Ecology 1965 areas potentially available Mead Ecology 1966 plant polygons Hoofd et al. Anatomy 1985 capillary domains Icke Astronomy 1987 Voronoi diagram

5. Why Should We Compute Them? Useful in a wide variety of applications Collision Detection Surface Reconstruction Robot Motion Planning Non-Photorealistic Rendering Surface Simplification Mesh Generation Shape Analysis

6. What Makes Them Useful? “Ultimate” Proximity Information Nearest Site Maximally Clear Path Density Estimation Nearest Neighbors

7. Outline • Generalized Voronoi Diagram Computation • Exact and Approximate Algorithms • Previous Work • Our Goal • Basic Idea • Our Approach • Basic Queries • Applications • Conclusion

8. Generalized Voronoi Diagram Computation“Exact” Algorithms • Previous work • Lee82 • Chiang92 • Okabe92 • Dutta93 • Milenkovic93 • Hoffmann94 • Sherbrooke95 • Held97 • Culver99 Computes Analytic Boundary

9. Previous Work: “Exact” Algorithms • Compute analytic boundaries but... • Boundaries composed of high-degree curves and surfaces and their intersections • Complex and difficult to implement • Robustness and accuracy problems

10. Generalized Voronoi Diagram Computation Approximate Algorithms Exact Algorithm Analytic Boundary Discretize Sites Discretize Space Previous work Lavender92, Sheehy95, Vleugels 95 & 96, Teichmann97

11. Previous Work: Approximate Algorithms • Provide practical solutions but... • Difficult to error-bound • Restricted to static geometry • Relatively slow

12. Our Goal • Simple to understand and implement • Easily generalized • Efficient and practical Approximate generalized Voronoi diagram computation that is: with all sources of error fully enumerated

13. Outline • Generalized Voronoi Diagram Computation • Basic Idea • Brute-force Algorithm • Cone Drawing • Graphics Hardware Acceleration • Our Approach • Basic Queries • Applications • Conclusion

14. Brute-force Algorithm Record ID of the closest site to each sample point Coarsepoint-samplingresult Finerpoint-samplingresult

15. Cone Drawing To visualize Voronoi diagram for points in 2D… Perspective, 3/4 view Parallel, top view Dirichlet 1850 & Voronoi 1908

16. Graphics Hardware Acceleration Simply rasterize the cones using graphics hardware Our 2-part discrete Voronoidiagram representation Color Buffer Depth Buffer Site IDs Distance Haeberli90, Woo97

17. Outline • Generalized Voronoi Diagram Computation • Basic Idea • Our Approach • Meshing Distance Function • Generalizations • 3D • Sources of Error • Basic Queries • Applications • Conclusion

18. The Distance Function Evaluate distance at each pixel for all sitesAccelerate using graphics hardware Point Line Triangle

19. Approximating the Distance Function Avoid per-pixel distance evaluationPoint-sample the distance functionReconstruct by rendering polygonal mesh Point Line Triangle

20. The Error Bound Error bound is determined by the pixel resolution  farthest distance a point can be from a pixel sample point Close-up of pixel grid

21. Meshing the Distance Function Shape of distance function for a 2D point is a cone Need a bounded-error tessellation of the cone

22. Shape of Distance Functions Sweep apex of cone along higher-order site to obtain the shape of the distance function

23. Example Distance Meshes

24. Curves Tessellate curve into a polylineTessellation error is added to meshing error

25. Weighted and Farthest Distance Nearest Weighted Farthest

26. 3D Voronoi Diagrams Graphics hardware can generate one 2D slice at a time Point sites

27. 3D Voronoi Diagrams Slices of the distance function for a 3D point site Distance meshes used to approximate slices

28. 3D Voronoi Diagrams Point Line segment Triangle 1 sheet of a hyperboloid Elliptical cone Plane

29. 3D Voronoi Diagrams Points and a triangle Polygonal model

30. Sources of Error • Distance Error • Meshing • Tessellation • Hardware Precision • Combinatorial Error • Distance • Pixel Resolution • Z-buffer Precision

31. Adaptive Resolution Zoom in to reduce resolution error...

32. Outline • Generalized Voronoi Diagram Computation • Basic Idea • Our Approach • Basic Queries • Nearest Site • Boundary Finding • Nearest-Neighbor Finding • Maximally Clear Point • Applications • Conclusion

33. Nearest Site Table lookup on query point

34. Boundary Finding • Isosurface extraction : boundary walking • Offset difference image to mark boundary pixels

35. Nearest-Neighbor Finding • Which colors touch in the image? • Walk the boundaries (like boundary finding)

36. Maximally Clear Point Point with the largest depth value (greatest distance)

37. Outline • Generalized Voronoi Diagram Computation • Basic Idea • Our Approach • Basic Operations • Applications • Motion Planning • Medial Axis Computation • Dynamic Mosaics • Conclusion

38. Real-time Motion Planning : Static Scene Plan motion of piano (arrow) through 100K triangle model Distance buffer of floorplan used as potential field

39. Real-time Motion Planning : Dynamic Scene Plan motion of music stand around moving furniture Distance buffer of floor-plan used as potential field

40. Medial Axis Computation Per-featureVoronoi diagram Per-feature-colordistance mesh Internal Voronoi diagram

41. Dynamic Mosaics 1000 moving points Source image Dynamic Mosaic Tiling Static mosaics by Paul Haeberli in SIGGRAPH ‘90

42. Outline • Generalized Voronoi Diagram Computation • Basic Idea • Our Approach • Basic Operations • Applications • Conclusion

43. Conclusion Meshing Distance Functions Graphics Hardware Acceleration Brute-force Approach + Fast and Simple, Approximate Generalized Voronoi Diagrams Bounded Error

44. Future Work • Improve distance meshing for 3D primitives • More applications • Motion planning with more degrees of freedom • Accelerate exact Voronoi diagram computation • Surface reconstruction • Medical imaging: segmentation and registration • Finite-element mesh generation

45. Acknowledgements Sarah Hoff Chris Weigle Stefan Gottschalk Mark Peercy UNC Computer Science SGI Advanced Graphics Berkeley Walkthrough Group

46. Acknowledgements Army Research Office National Institute of Health National Science Foundation Office of Naval Research Intel

47. Live Demo...