COMP-766: Shape Analysis in Computer Vision

Timings: T/Th: to be determined
Room: McConnell 320
Instructor: Kaleem Siddiqi
Office: MC-420
Office Hrs: W: 09:00 am - 10:30 noon
Phone: 398-3371

This course is being offered for the first time in 5 years during the Winter 2009-2010 term. I used to teach it regularly before then.

Course description

Object shape lies at the interface between vision and cognition, yet, truly general purpose theories of shape for applications in industry, bio-medicine, and robotics, have been notoriously difficult to formulate. In this research seminar we shall attempt to articulate the critical aspects of such a theory. The course will emphasize the interdisciplinary nature of the problem, drawing on insights from diverse areas ranging from psychology to singularity theory and classical mechanics. Topics to be covered include (but are not limited to): early vision, curve inference and fragment grouping, variational methods, geometric scale spaces, curve and surface evolution, level set techniques, shape segmentation, shape matching, object recognition.

Course format

The course will be organized around lectures as well as discussions of journal arcticles and papers which will be distributed on a weekly basis. Students will be expected to prepare short (2 page) critical summaries of selected articles and to participate actively in class. Whereas there is no assigned textbook, relevant reference material will be placed on reserve in the physical sciences and engineering library. Some background in differential equations, differential geometry and linear algebra will be helpful. A significant aspect of this course will be an independent research project, carried out in consultation with the instructor, on which each student will be expected to make a presentation at the end of the term.

Course evaluation

  • Research project: 40%
  • Final examination: 20%
  • Assignments: 20%
  • Critical summaries: 20%
  • There will be two assignments worth 10% each. In addition you will be required to write critical summaries (no more than two single-spaced pages each) of 5 articles of your choice from the set of readings posted under the calendar. Each critique will comprise 4% of your total mark.

           Student Guide to Avoid Plagiarism




  • Trace Inference (PS) (PDF)
  • Relaxation Labeling (PS) (PDF)
  • Area/Length Flows (PS) (PDF)
  • Scale Spaces
  • Scale Space Notes (PDF)

  • News

    Recent Research Projects

    Below is a set of links to some of the research projects completed by students who took this course last year. I am grateful to them for making this material available. 2002-2003 Winter Term
  • Maxime Descoteaux: Affine and Euclidean Geometric Heat Equation for Anisotropic Smoothing (HTML)/ (PDF)/ Experimental results
  • Simon Lacoste-Julien: Geometrical Analysis of an Area Minimization Flow (HTML)/ (PDF)
  • Cathy Laporte: Context-based aspect graphs for active object recognition (HTML)
  • Moses Mathur: Variational Problems and PDE's on Implicit Surfaces (HTML)
  • Ajit Rajwade: Illumination invariance in face recognition (DOC).
  • Sandra Skaff: Perceptual illusions arising from dot displays (PDF).
  • 2003-2004 Fall Term
  • Shiyan Hu: Stochastic Completion Field With Probabilistic Transition (PDF)
  • Tran-Quan Luong: An Exploration of Stochastic Completion Fields (PDF)
  • Scott McClosskey: Shape From Pictures (PDF)
  • Frank Riggi: Matching Shapes by Probabilistic Graph Matching (PDF)

  • Links

  • All IEEE publications are available at IEEE EXPLORE .
  • Many science articles are available at JSTOR .
  • International Journal of Computer Vision Home Page .
  • McGill Libraries . Click on Muse and then on Journal Titles to do a search.
  • Elsevier Science Journals .
  • Classics in the History of Psychology .
  • Computer Vision Home Page.