COMP-507A:
Computational Geometry
"Where there is matter, there is geometry." - Johannes
Kepler

Course: Computer
Science
COMP-507
Title: Computational Geometry (3 credits, 3
hours)
Time & Place:
Instructor: Godfried
Toussaint
Phone:
Office hours:
Teaching Assistant:
Course prerequisites:
- COMP-360 (Algorithms) or:
- Knowledge of design and analysis of
algorithms
("Big
O" notation, etc.)
- Knowledge of data structures (stacks,
linked-lists,
arrays, balanced trees, etc.)
- Knowledge of probability and statistics.
Performance assessment:
- Two
in-class
75-minute
tests at 24% each (after 4 and 9
weeks approximately).
- One oral
in-class presentation of an approved
journal paper, at 20% (at the end of
term).
- One Web
project at a total of 32%. The Web
project involves
publishing a tutorial introduction
to a simple idea and is divided into two parts: the HTML
document (counts for 12%) and the interactive
Java applet (counts for 20%). Both the HTML document and the
Java
applet are due November 29 and
the
entire finished project must be installed in the Computational
Geometry Lab by that date.
- Four or five practice assignments (not
collected,
not marked,
and not counted). However, students who wish may hand in their
assignments
to the TA's for feedback. The TA will give tutorials on these as
necessary.
Solutions will be handed out on the "due" dates.
Text book and course material:
Useful books:
- Mark de Berg, et al., Computational
Geometry: Algorithms and Applications, Springer Verlag, 1997.
- Franco
P.
Preparata and Michael
I. Shamos, Computational Geometry
, Springer-Verlag, 1985.
- J. O'Rourke, Art
Gallery Theorems and Algorithms, Oxford University Press, 1987.
- G. T. Toussaint, Ed., Computational
Geometry, North-Holland, 1985.
- G. T. Toussaint, Ed., Computational
Morphology, North-Holland, 1988.
- J. E. Goodman and J. O'Rourke, Eds., Handbook
of Discrete and Computational Geometry, CRC Press, Boca Raton,
1997.
- Ming C. Lin and Dinesh Manocha, (Eds.), Applied
Computational Geometry, Springer-Verlag, 1996.
Course Outline:
- Classical geometry and basic concepts. Ancient
and
modern
models of geometric computation. Point inclusion problems. Convexity
testing.
Computing and updating triangulations of polygons, sets of line
segments
and sets of points. Computing distances between sets. Art-gallery
theorems.
Relationships between computational complexity, unimodality of
functions
and convexity. Computing convex hulls of polygons and point sets.
Hidden
line problems. Proximity graphs and their applications. Facility
location
and linear programming. Mobility of objects in space. Removing
non-degeneracy
assumptions. Computing shortest transversals of sets. Arrangements of
lines
and their applications. Visualization via nice projections.
Reminder:
- McGill University values
academic integrity.
Therefore all students must understand the meaning and consequences of
cheating, plagiarism and other academic offences under the Code of
Student
Conduct and Disciplinary Procedures (see www.mcgill.ca/integrity
for more information).