|
| Course Description
Lectures: HNE 030, Tue, Thu 2:30-4:00
This a seminar course that examines the classical statistical
approaches to visual motion analysis. Several areas of visual motion will
be examined like 3-D structure and motion estimation, optical flow,
segmentation and tracking. A variety of statistical techniques will be
presented with emphasis on how they can be applied on vision
problems. These techniques include Least Squares, Clustering, Kalman
Filter, Maximum Likelihood, Maximum A Posteriori, Expectation
Maximization, Robust Methods etc. Approximately half the lectures will be
on background theory by the instructor and the other half literature
review by the students.
Evaluation
Every student will write 3 papers, two of them short literature reviews,
that cover a rather narrow area, are based on several papers and are
presented in class while the third (last) is much longer, and can be
either a literature review or an original but well contained research
topic. The short papers carry a weight of 25% and the long 35%. All
presentations are 20 minutes. A midterm test scheduled sometime after most
of the lectures by the instructor will carry weight 15%.
Last
Modified: Jan 4 2011 |
