Computational Geometry: Triangulations and Art Gallery Guarding

1
Computational Geometry
Triangulations and
Guarding Art Galleries
Michael T. Goodrich
with slides by Carola Wenk, Tulane Univ., and Subhash Suri, UCSB
 
2
 
Guarding an Art Gallery
 
Problem:
 Given the floor plan of an art gallery, place (a small number
of) cameras/guards such that every point in the art gallery can be seen
by some camera.
 
Art Gallery
 
Floor plan
 
Polygons
 
A 
polygonal curve 
is a finite chain of line segments.
Line segments called 
edges
, their endpoints called
vertices
.
A 
simple polygon 
is a closed polygonal curve without
self-intersection.
 
3
4
Guarding an Art Gallery:
Computational Geometry version
Problem:
 Given the floor plan of an art gallery as a simple polygon 
P
in the plane with 
n
 vertices. Place (a small number of) cameras/guards
on vertices of 
P
 such that every point in 
P
 can be seen by some
camera.
5
Guarding an Art Gallery
There are many different variations:
Guards on vertices only, or in the interior as well
Guard the interior or only the walls
Stationary versus moving or rotating guards
Finding the minimum number of guards is
NP-hard (Aggarwal ’84)
First subtask: Bound the number of guards
that are necessary to guard a polygon in the
worst case.
 
6
 
Guard Using Triangulations
 
Decompose the polygon into shapes that are easier to handle:
triangles
A 
triangulation
 of a polygon 
P
 is a decomposition of 
P
 into
triangles whose vertices are vertices of 
P
. In other words, a
triangulation is a maximal set of non-crossing diagonals.
 
diagonal
7
Guard Using Triangulations
 
A polygon can be triangulated in many different ways.
Guard polygon by putting one camera in each triangle:
Since the triangle is convex, its guard will guard the
whole triangle.
 
8
 
Triangulations of Simple Polygons
 
Theorem 1:
  Every simple polygon admits a
triangulation, and any triangulation of a simple
polygon with 
n
 vertices consists of exactly 
n
-2
triangles.
 
Proof:
 By induction.
n
=3
:
n
>3
: Let 
u
 be leftmost vertex, and 
v
and 
w
 adjacent to 
v
. If 
vw
 does not
intersect boundary of 
P
: #triangles
= 
1
 for new triangle + 
(
n
-1)-2
 for
remaining polygon = 
n
-2
 
u
 
w
 
v
 
P
 
9
 
Triangulations of Simple Polygons
 
Theorem 1:
  Every simple polygon admits a
triangulation, and any triangulation of a simple
polygon with 
n
 vertices consists of exactly 
n
-2
triangles.
 
If 
vw
 intersects boundary of 
P
: Let 
u’
u
be the the vertex furthest to the left of 
vw
.
Take 
uu
 as diagonal, which splits 
P
 into
P
1
 and 
P
2
.
 
#triangles in 
P
 
=
 #triangles in 
P
1
 
+
 #triangles in 
P
2
 
= 
#vertices in 
P
1
 
– 2 +
 #vertices in 
P
2  
- 2
 
= 
n 
+ 2 - 4 = 
n
-2
 
u
 
w
 
v
 
u’
 
P
 
P
1
 
P
2
 
Example
 
Polygon below has n = 13, and 11 triangles.
 
10
 
11
 
3-Coloring
 
A 3-coloring of a graph is an assignment of
one out of three colors to each vertex such
that adjacent vertices have different colors.
 
12
 
3-Coloring Lemma
 
Lemma:
 For every triangulated polgon there is a 3-coloring.
 
Proof:
 Consider the 
dual graph
 of the triangulation:
vertex for each triangle
edge for each edge between triangles
 
13
 
3-Coloring Lemma
 
Lemma:
 For every triangulated polgon there is a 3-coloring.
 
The dual graph is a tree (connected acyclic graph): Removing
an edge corresponds to removing a diagonal in the polygon
which disconnects the polygon and with that the graph.
14
3-Coloring Lemma
Lemma:
 For every triangulated polgon there is a 3-coloring.
Traverse the tree  (DFS). Start with a triangle and give
different colors to vertices. When proceeding from one
triangle to the next, two vertices have known colors, which
determines the color of the next vertex.
15
Art Gallery Theorem
Theorem 2:
 For any simple polygon with 
n
 vertices
       guards are sufficient to guard the whole polygon.
There are polygons for which       guards are necessary.
Proof:
 For the upper bound, 3-color any triangulation of the
polygon and take the color with the minimum number of
guards.
Lower bound:
spikes
 
Need one guard per spike.
 
16
 
Triangulating a Polygon
 
There is a simple 
O(
n
2
)
 time algorithm based on the
proof of Theorem 1.
There is a very complicated 
O(
n
)
 time algorithm
(Chazelle ’91) which is impractical to implement.
We will discuss a practical 
O(
n
 log 
n
)
 time
algorithm:
1.
Split polygon into 
monotone polygons
 (
O(
n 
log
 n
)
time)
2.
Triangulate each monotone polygon (
O(
n
)
 time)
 
17
 
Monotone Polygons
 
A simple polygon 
P
 is called 
monotone with respect to a
line
 
l
 iff for every line 
l’
 perpendicular to 
l
 the intersection of
P
 with 
l’
 is connected.
P is 
x
-monotone
 iff 
l
 = 
x
-axis
P is 
y
-monotone
 iff 
l
 = 
y
-axis
 
l’
 
l
 
x-monotone
(monotone
w.r.t 
l
)
 
18
 
Monotone Polygons
 
A simple polygon 
P
 is called 
monotone with respect to a
line
 
l
 iff for every line 
l’
 perpendicular to 
l
 the intersection of
P
 with 
l’
 is connected.
P is 
x
-monotone
 iff 
l
 = 
x
-axis
P is 
y
-monotone
 iff 
l
 = 
y
-axis
 
l’
 
l
 
NOT x-monotone
(NOT monotone
w.r.t 
l
)
 
19
 
Monotone Polygons
 
A simple polygon 
P
 is called 
monotone with respect to a
line
 
l
 iff for every line 
l’
 perpendicular to 
l
 the intersection of
P
 with 
l’
 is connected.
P is 
x
-monotone
 iff 
l
 = 
x
-axis
P is 
y
-monotone
 iff 
l
 = 
y
-axis
 
l
 
NOT monotone w.r.t
any line 
l
 
l’
20
Test Monotonicity
 
How to test if a polygon is 
x
-monotone?
Find leftmost and rightmost vertices, 
O(
n
)
 time
 Splits polygon boundary in upper chain and lower chain
Walk from left to right along each chain, checking that x-
coordinates are non-decreasing. 
O(
n
)
 time.
 
21
 
Triangulating a Polygon
 
There is a simple 
O(
n
2
)
 time algorithm based on the
proof of Theorem 1.
There is a very complicated 
O(
n
)
 time algorithm
(Chazelle ’91) which is impractical to implement.
We will discuss a practical 
O(
n
 log 
n
)
 time
algorithm:
1.
Split polygon into 
monotone polygons
 (
O(
n 
log
 n
)
time)
2.
Triangulate each monotone polygon (
O(
n
)
 time)
22
Triangulate an 
l
-Monotone Polygon
Using a greedy plane sweep in direction 
l
Sort vertices by increasing 
x
-coordinate (merging the upper and lower
chains in 
O(
n
)
 time)
Greedy: Triangulate everything you can to the left of the sweep line.
 
1
 
2
 
3
 
4
l
 
5
 
6
 
7
 
8
 
9
 
10
 
11
 
12
 
13
23
Triangulate an 
l
-Monotone Polygon
Store stack (sweep line status) that contains vertices that have
been encountered but may need more diagonals.
 
Maintain invariant:
 Un-triangulated region
has a 
funnel shape
. The funnel consists of an
upper and a lower chain. One chain is one line
segment. The other is a 
reflex chain
 (interior
angles >180°) which is stored on the stack.
 
Update, case 1: new vertex lies on chain
opposite of reflex chain. Triangulate.
24
Triangulate an 
l
-Monotone Polygon
Update, case 2: new vertex lies on reflex chain
 
Case a: The new vertex lies above line through
previous two vertices: Triangulate.
 
Case b: The new vertex lies below line through
previous two vertices: Add to reflex chain (stack).
 
25
 
Triangulate an 
l
-Monotone Polygon
 
Distinguish cases in constant time using half-plane
tests
Sweep line hits every vertex once, therefore each
vertex is pushed on the stack at most once.
Every vertex can be popped from the stack (in order to
form a new triangle) at most once.
 Constant time per vertex
 O(
n
)
 total runtime
 
Example
 
26
 
27
 
Triangulating a Polygon
 
There is a simple 
O(
n
2
)
 time algorithm based on the
proof of Theorem 1.
There is a very complicated 
O(
n
)
 time algorithm
(Chazelle ’91) which is impractical to implement.
We will discuss a practical 
O(
n
 log 
n
)
 time
algorithm:
1.
Split polygon into 
monotone polygons
 (
O(
n 
log
 n
)
time)
2.
Triangulate each monotone polygon (
O(
n
)
 time)
 
28
 
Trapezoidal Decomposition
 
Extend a vertical ray up and/or down into the interior of
the polygon from each vertex until it hits the boundary
 
29
 
Trapezoidal Decomposition
 
Use plane sweep algorithm.
At each vertex, extend vertical line until it hits a
polygon edge.
Each face of this decomposition is a trapezoid; which
may degenerate into a triangle.
Time complexity is O(n log n).
 
30
 
Computing a Monotone Subdivision
 
Monotone subdivision:
 subdivision of the simple
polygon 
P
 into monotone pieces
 
split vertex
 
merge vertex
 
interior
 
31
 
Monotone Subdivision
 
Call a reflex vertex with both rightward (leftward) edges a
split
 (
merge
) vertex.
Non-monotonicity comes from split or merge vertices.
Add a diagonal to each to remove the non-monotonicity.
To each split (merge) vertex, add a diagonal joining it to the
polygon vertex of its left (right) trapezoid. Output as a
DCEL.
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Explore the concepts of triangulations and guarding art galleries in computational geometry. Learn about the problem of placing cameras or guards strategically in an art gallery to ensure every point is visible. Discover how polygons are defined, the variations in guarding strategies, and the use of triangulations to decompose polygons for efficient guarding techniques.

  • Computational Geometry
  • Triangulations
  • Art Gallery Guarding
  • Polygons
  • Camera Placement

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  1. Computational Geometry Triangulations and Guarding Art Galleries Michael T. Goodrich with slides by Carola Wenk, Tulane Univ., and Subhash Suri, UCSB 1

  2. Guarding an Art Gallery Problem: Given the floor plan of an art gallery, place (a small number of) cameras/guards such that every point in the art gallery can be seen by some camera. Art Gallery Floor plan 2

  3. Polygons A polygonal curve is a finite chain of line segments. Line segments called edges, their endpoints called vertices. A simple polygon is a closed polygonal curve without self-intersection. 3

  4. Guarding an Art Gallery: Computational Geometry version Problem: Given the floor plan of an art gallery as a simple polygon P in the plane with n vertices. Place (a small number of) cameras/guards on vertices of P such that every point in P can be seen by some camera. 4

  5. Guarding an Art Gallery There are many different variations: Guards on vertices only, or in the interior as well Guard the interior or only the walls Stationary versus moving or rotating guards Finding the minimum number of guards is NP-hard (Aggarwal 84) First subtask: Bound the number of guards that are necessary to guard a polygon in the worst case. 5

  6. Guard Using Triangulations Decompose the polygon into shapes that are easier to handle: triangles A triangulation of a polygon P is a decomposition of P into triangles whose vertices are vertices of P. In other words, a triangulation is a maximal set of non-crossing diagonals. diagonal 6

  7. Guard Using Triangulations A polygon can be triangulated in many different ways. Guard polygon by putting one camera in each triangle: Since the triangle is convex, its guard will guard the whole triangle. 7

  8. Triangulations of Simple Polygons Theorem 1: Every simple polygon admits a triangulation, and any triangulation of a simple polygon with n vertices consists of exactly n-2 triangles. Proof: By induction. n=3: n>3: Let u be leftmost vertex, and v and w adjacent to v. If vw does not intersect boundary of P: #triangles = 1 for new triangle + (n-1)-2 for remaining polygon = n-2 v P u w 8

  9. Triangulations of Simple Polygons Theorem 1: Every simple polygon admits a triangulation, and any triangulation of a simple polygon with n vertices consists of exactly n-2 triangles. If vw intersects boundary of P: Let u u be the the vertex furthest to the left of vw. Take uu as diagonal, which splits P into P1 and P2. #triangles in P = #triangles in P1 + #triangles in P2 = #vertices in P1 2 + #vertices in P2 - 2 = n + 2 - 4 = n-2 P v P1 u u P2 w 9

  10. Example Polygon below has n = 13, and 11 triangles. 10

  11. 3-Coloring A 3-coloring of a graph is an assignment of one out of three colors to each vertex such that adjacent vertices have different colors. 11

  12. 3-Coloring Lemma Lemma: For every triangulated polgon there is a 3-coloring. Proof: Consider the dual graph of the triangulation: vertex for each triangle edge for each edge between triangles 12

  13. 3-Coloring Lemma Lemma: For every triangulated polgon there is a 3-coloring. The dual graph is a tree (connected acyclic graph): Removing an edge corresponds to removing a diagonal in the polygon which disconnects the polygon and with that the graph. 13

  14. 3-Coloring Lemma Lemma: For every triangulated polgon there is a 3-coloring. Traverse the tree (DFS). Start with a triangle and give different colors to vertices. When proceeding from one triangle to the next, two vertices have known colors, which determines the color of the next vertex. 14

  15. Art Gallery Theorem Theorem 2: For any simple polygon with n vertices guards are sufficient to guard the whole polygon. There are polygons for which guards are necessary. n 3 n 3 Proof: For the upper bound, 3-color any triangulation of the polygon and take the color with the minimum number of guards. Lower bound: n 3 spikes Need one guard per spike. 15

  16. Triangulating a Polygon There is a simple O(n2) time algorithm based on the proof of Theorem 1. There is a very complicated O(n) time algorithm (Chazelle 91) which is impractical to implement. We will discuss a practical O(n log n) time algorithm: 1. Split polygon into monotone polygons (O(n log n) time) 2. Triangulate each monotone polygon (O(n) time) 16

  17. Monotone Polygons A simple polygon P is called monotone with respect to a linel iff for every line l perpendicular to l the intersection of P with l is connected. P is x-monotone iff l = x-axis P is y-monotone iff l = y-axis l x-monotone (monotone w.r.t l) l 17

  18. Monotone Polygons A simple polygon P is called monotone with respect to a linel iff for every line l perpendicular to l the intersection of P with l is connected. P is x-monotone iff l = x-axis P is y-monotone iff l = y-axis l NOT x-monotone (NOT monotone w.r.t l) l 18

  19. Monotone Polygons A simple polygon P is called monotone with respect to a linel iff for every line l perpendicular to l the intersection of P with l is connected. P is x-monotone iff l = x-axis P is y-monotone iff l = y-axis l NOT monotone w.r.t any line l l 19

  20. Test Monotonicity How to test if a polygon is x-monotone? Find leftmost and rightmost vertices, O(n) time Splits polygon boundary in upper chain and lower chain Walk from left to right along each chain, checking that x- coordinates are non-decreasing. O(n) time. 20

  21. Triangulating a Polygon There is a simple O(n2) time algorithm based on the proof of Theorem 1. There is a very complicated O(n) time algorithm (Chazelle 91) which is impractical to implement. We will discuss a practical O(n log n) time algorithm: 1. Split polygon into monotone polygons (O(n log n) time) 2. Triangulate each monotone polygon (O(n) time) 21

  22. Triangulate an l-Monotone Polygon Using a greedy plane sweep in direction l Sort vertices by increasing x-coordinate (merging the upper and lower chains in O(n) time) Greedy: Triangulate everything you can to the left of the sweep line. 7 12 11 10 2 34 5 9 8 1 6 13 l 22

  23. Triangulate an l-Monotone Polygon Store stack (sweep line status) that contains vertices that have been encountered but may need more diagonals. Maintain invariant: Un-triangulated region has a funnel shape. The funnel consists of an upper and a lower chain. One chain is one line segment. The other is a reflex chain (interior angles >180 ) which is stored on the stack. Update, case 1: new vertex lies on chain opposite of reflex chain. Triangulate. 23

  24. Triangulate an l-Monotone Polygon Update, case 2: new vertex lies on reflex chain Case a: The new vertex lies above line through previous two vertices: Triangulate. Case b: The new vertex lies below line through previous two vertices: Add to reflex chain (stack). 24

  25. Triangulate an l-Monotone Polygon Distinguish cases in constant time using half-plane tests Sweep line hits every vertex once, therefore each vertex is pushed on the stack at most once. Every vertex can be popped from the stack (in order to form a new triangle) at most once. Constant time per vertex O(n) total runtime 25

  26. Example 26

  27. Triangulating a Polygon There is a simple O(n2) time algorithm based on the proof of Theorem 1. There is a very complicated O(n) time algorithm (Chazelle 91) which is impractical to implement. We will discuss a practical O(n log n) time algorithm: 1. Split polygon into monotone polygons (O(n log n) time) 2. Triangulate each monotone polygon (O(n) time) 27

  28. Trapezoidal Decomposition Extend a vertical ray up and/or down into the interior of the polygon from each vertex until it hits the boundary 28

  29. Trapezoidal Decomposition Use plane sweep algorithm. At each vertex, extend vertical line until it hits a polygon edge. Each face of this decomposition is a trapezoid; which may degenerate into a triangle. Time complexity is O(n log n). 29

  30. Computing a Monotone Subdivision Monotone subdivision: subdivision of the simple polygon P into monotone pieces split vertex interior merge vertex 30

  31. Monotone Subdivision Call a reflex vertex with both rightward (leftward) edges a split (merge) vertex. Non-monotonicity comes from split or merge vertices. Add a diagonal to each to remove the non-monotonicity. To each split (merge) vertex, add a diagonal joining it to the polygon vertex of its left (right) trapezoid. Output as a DCEL. 31

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