The web project is to be a tutorial of a topic in pattern recognition. This consists of an HTML document worth 20% and a JAVA applet worth 15% (due at the end of the term). You are not expected to do original research here, just create a tutorial like the ones used as reading material.
Your project should be easier to read than the paper(s) it is based on. Don't copy endless series of equations and text. Add lots of pictures, examples, moving gifs and color. Explain things in a natural manner, instead of using lots of notation.

Your applet must work on machines at the CS labs, as well as on windows. Test a basic version of your applet well in advance of the deadline!!!
The minimum requirement is that the user can follow the steps of some procedure. In other words, there may be no user interaction, but you have one (or preferably more) example illustrated in great detail. There should be some advantage of your applet over a gif movie.
A good applet will allow user interaction. This does not mean being able to choose among 2-3 examples. The user should be able to enter/delete objects and so on.
If applicable..... An excellent applet is one which can be used multiple times by the same user, and each time they can potentially construct/discover something new. This means that the applet is a (pattern recognition) tool, not just an example.

Projects from past years
More projects from cs507 (identical project scheme)

After you have ENTIRELY finished your project, you must give me a .tar.gz file: Place all your files in a directory named after you (example: if your name is James Bond, then "mkdir JamesBond" ). Then "tar cvf JamesBond.tar Jamesbond" , "gzip JamesBond.tar" and send me the file JamesBond.tar.gz by email.
Note: exact commands may differ slightly. For example you might need "tar -cvf".
Your starting page must be called welcome.html - so that a link of type http:cgm.cs....../JamesBond will open up your project.
If projects by two people are allowed, just use either name.

Please include your names, the title, and contact information in your html text.

Projects taken
  • Derek Rivait: The Euclidean algorithm and traditional musical rhythms
  • Alexandre Fortin: Relative hulls
  • Ran Chen: Distance transforms and Rosenfeld's algorithm for skeletonization
  • Jean-Philippe Gravel and Donovan Parks: Corner detection and interest point algorithms
  • Michael Imbrogno: Efficient shape matching through model-based shape recognition
  • Derek Johns: Line-sweep algorithm for computing the Voronoi diagram
  • Xiaopeng Qu: Implementation of contour tracing and hysteresis smoothing
  • Felix-Olivier Duguay: Using neural networks to fit a continuous curve with a polynomial
  • Daniel Burfoot: Recognition of Chinese characters with application to online learning
  • Pawel Kowalczyk: Depth
  • Svetlana Stolpner: An efficiently computable metric for comparing polygonal shapes
  • Cory McKay: Forward-Backward and Floating Point feature selection
  • Perouz Taslakian: Reconfiguring trianglulations with edge-flips and point moves

    Some available projects