voronoi diagram (supplemental) the universal spatial data structure (franz aurenhammer)
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Voronoi Diagram (Supplemental)
The Universal Spatial Data Structure (Franz Aurenhammer)
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Outline
Voronoi and DelaunayFacility location problemNearest neighborFortune’s algorithm revisitedGeneralized Voronoi diagrams
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Voronoi Diagram
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Dual: Delaunay Triangulation
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Fall 2005 5
Facility Location Problems
Determine a location to minimize the distance to its furthest customerMinimum enclosing circle
Determine a location whose distance to nearest store is as large as possibleLargest empty circle
ip
jp
kp
q
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Facility Location (version 2)
Seek location for new grocery store, whose distance to nearest store is as large as possible — center of largest empty circleOne restriction: center in convex hull of the sites
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Facility Location (cont)
Center in hull: p must be coincident with a voronoi vertex
Center on hull: p must lie on a voronoi edge
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Largest Empty Circle
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Nearest Neighbor Search
A special case of point-location problem where every face in the subdivision is monotoneUse chain method to get O(log n) time complexity for query
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Fall 2005 18
Cluster Analysis
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Closest Pairs
In collision detection, two closest sites are in greatest danger of collisionNaïve approach: (n2)
Each site and its closest pair share an edge check all Voronoi edges O(n)Furthest pair cannot be derived directly from the diagram
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Motion Planning (translational)
Collision avoidance:
stay away from obstacle
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Fortune’s Algorithm Revisited
ConesIdeaH/W implementation
The curve of intersection of two cones projects to a line.
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45 deg Cone
distance=heightsite
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Cone (cont)
intersection of cone equal-distance point
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Cone (cont)When viewed from –Z, we got colored V-cells
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Nearest Distance Function
Viewed from here[less than]
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Furthest Distance Function
Viewed from here[greater than]
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Fortune’s Algorithm (Cont)
Cone slicing
Cone cut up by sweep plane and L are sweeping toward the right.
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Fortune’s Algorithm (Cont)
Viewed from z = -, The heavy curve is the parabolic front.
How the 2D algorithm and
the 3D cones are related…
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Generalized Voronoi Diagram
V(points), Euclidean distance V(points, lines, curves, …)Distance function: Euclidean, weighted, farthest
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Brute Force Method
Record ID of the closest site to each sample
point
Coarsepoint-sampling
result
Finerpoint-sampling
result
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Graphics Hardware Acceleration
Our 2-part discrete Voronoidiagram representation
Distance
Depth Buffer
Site IDs
Color Buffer
Simply rasterize the cones using gra
phics hardware
Haeberli90, Woo97
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Algorithm
Associate each primitive with the corresponding distance meshRender each distance mesh with depth test onVoronoi edges: found by continuation methods
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Ex: Voronoi diagram between a point and a line
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Distance Meshes
linecurve
polygon
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Applications (Mosaic)
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Hausner01, siggraph
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Medial Axis Computation
Medial axes as part of Voronoi diagram
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Piano Mover: Real-time Motion Planning (static and dynamic)
Plan motion of piano through 100K triangle model
Distance buffer of floorplan used as potential field
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Variety of Voronoi Diagram
(regular) Voronoi diagram
Furthest distance Voronoi diagram
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Minimum Enclosing Circle
Center of MEC is at the vertex of furthest site Voronoi diagram