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What is Computational Geometry

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Title: What is Computational Geometry


1
What is Computational Geometry
  • Ref Godfried T. Toussaint

2
The Problem
  • Given a line (yaxb) and a point p (xp,yp),
    determine whether the point is above/below the
    line
  • Solution 1
  • Set xz xp
  • Compute yz
  • Compare yz and yp

3
Alternate Solutions
Originality of this formula
  • Signed area
  • Negative if CW
  • Positive if CCW
  • How do you compare these two algorithms in terms
    of
  • Robustness?
  • Efficiency?

Consider special cases
4
Possible Definitions of CGeom
  • The science concerned with computing geometric
    properties of sets of geometric objects in space
  • The design and analysis of algorithms for solving
    geometric problems
  • The study of the inherent computational
    complexity of geometric problems under varying
    models of computation
  • Runs faster, requires less memory space and more
    robust wrt numerical errors

5
Modern Computational Geometry
  • Ph.D. thesis of M. Shamos (Yale, 1978)
  • Has been around for more than 2600 years starting
    with the Greeks
  • Difference
  • The size of input to an algorithm (n)
  • (Today) Hundreds, thousands, or millions
  • The dimension of a problem (d)
  • (Greek) Euclidean two and three space
  • (Today) not limited to the exploration of low
    dimensional problems non-Euclidean, higher
    dimension

6
The Complexity of Algorithm
  • Ex Convex Hull
  • (naïve algorithm)
  • C(n) the total number of primitive operation
    required

7
Big O, Big Omega, and C(n)
  • Big O
  • A simplified expression with only the dominant
    terms, dropping the coefficient
  • The contribution that Shamos made was the
    emphasis on including with each algorithm a
    complexity analysis in terms of Big O notation
    and the introduction of lower bounds on the
    complexity of geometric problems
  • Big Omega W
  • Lower bound on the time complexity of the problem
  • A statement about the problem (not the algorithm)
  • Optimal when complexity function of the
    algorithm matches the complexity function of the
    problem

8
The Domain of CG
  • Geometric Probing
  • Art Gallery Theorems and Algorithms
  • Computer Graphics
  • Geometric Modeling
  • Computer Vision
  • Robotics
  • Dynamic CG
  • Parallel CG
  • Isothetic CG
  • Numerical CG
  • Geodesic CG
  • See also
  • Eppsteins Geometry in Action

9
Minimax Facility Location Problem
  • Determine location X where a facility should be
    located so as to minimize the distance from X to
    its furthest customer
  • Find the smallest circle that encloses a given
    set of n points

10
Geometric Probing
  • Implement a QC procedure to determine circularity
    of rings
  • For smooth convex shape, the verification of D in
    sufficient directions should work
  • Apply 3 probes, 60 degrees apart
  • Does this work?
  • Challenger anecdote

11
Geometric Probing (cont)
  • Reuleaux triangle
  • (construction)
  • Known as constant diameter shape
  • Smooth rolling, yet highly non-circular
  • Demonstrates that any number of such probes is
    insufficient to determine circularity

Verify the distance between any parallel lines is
D
12
Theory of Geometric Probing
  • The determination of the number of probes that
    are necessary and sufficient to determine an
    object completely
  • The design of efficient algorithms for actually
    carrying out the probing strategies
  • Computer vision, pattern recognition, QC, robotics
  • References
  • Steven Skiena Problems in Geometric Probing.
    Algorithmica 4(4) 599-605 (1989)
  • Skiena Interactive Reconstruction via Geometric
    Probing (1992)

13
Art Gallery Problem
  • 1973 Victor Klee poses the problem
  • Given n arbitrarily shaped gallery, what is the
    minimum number of cameras required to guard the
    interior of an n-wall gallery?
  • 1975, Vasek Chvatals theorem n/3 are always
    sufficient and sometimes necessary.

14
Observation
15
Computer Graphics
  • Hidden line problem hidden surface removal
    visibility problem

16
Isothetic Computational Geometry
  • Also rectilinear computational geometry
  • Often greatly simplifies the algorithm
  • Image processing, VLSI design

17
Geodesic
  • Euclidean distance between two points no longer a
    useful measure
  • Geodesic distance the length of the shortest
    path between the two points that avoids obstacles
  • Geodesic convex hull (also relative convex hull)
  • Given a set S of n points inside a simple polygon
    P of n vertices, the relative convex hull of X
    (relative to P) is the minimum perimeter circuit
    that lies in p and encloses S.

18
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19
Homeworks
  • Verify that the signed area of triangle is
    correct.
  • Verify that for Reuleaux triangles, the distance
    between any pair parallel lines is constant.
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