CMPT 882: Recognition Problems in Computer Vision, Summer 2009 - Project

The intent of the course project is to give you some practice at doing research. If you are a new graduate student, this could be your first time doing research. The important thing to learn is the correct methodology for doing research.

The key components, and those on which you will be graded, are:

• Choosing the right problem/methodology. This is one of the most challenging aspects of research. Do not choose something too hard nor too simple. You have submitted project proposals so that I can make sure you're on the right track.

  Please see me during office hours if you have questions along the way.

• What has been done before? A month in the lab can save you a day in the library. This is a course project, and not a peer-reviewed paper, but you should be aware of the most closely related work. In fact, a perfectly good project is to implement a previous paper (of non-trivial complexity). I expect roughly 3-5 citations to other work as part of your project report.

  You must also maintain high standards of academic integrity. Standing on the shoulders of giants is highly recommended, just make it clear who these giants are. If you use someone else's code, you must provide a citation. If you use text/equations from someone else's paper, you must cite and quote it. If you use figures from another paper, you must clearly state such.

• Comparative experiments. You must compare what you have done to at least one other method to know if anything interesting has been achieved. Proper experiments should only change one component at a time (e.g. same classifier, different features). You should also study different parameters of algorithms to ascertain sensitivity.

  You will not be graded on the quality of your results, but on the quality of your experimental methodology.

• Quality of exposition. If you write a paper and nobody can read it, does it make a contribution? Clearly state the problem you worked on, the methods you used, who has done what before, what was the intent of your project, which datasets, and what parameters you used. Use a spell-checker, create figures with legible fonts and labelled axes, and provide figures visualizing your results.

The project report should be prepared using the CVPR style files. The page limit for the project report is 6 pages in this format. You must submit the report electronically on the submission server in PDF format.

The report is due at 11:59pm on August 6. This deadline will be horribly strict.