ECSE 626 Statistical Computer Vision (4 credits)

Note: This is the 2016–2017 edition of the eCalendar. Update the year in your browser's URL bar for the most recent version of this page, or click here to jump to the newest eCalendar.

Offered by: Electrical & Computer Engr (Faculty of Engineering)

Administered by: Graduate Studies

Overview

Electrical Engineering : An overview of statistical techniques as applied to computer vision and image processing. Topics include regularization, Kalman filtering, Markov-Chain Monte Carlo methods, importance sampling and particle filtering, Markov Random fields, parameter estimation, mean-field techniques, stochastic and deterministic annealing, principal and independent components analysis.

Terms: This course is not scheduled for the 2016-2017 academic year.

Instructors: There are no professors associated with this course for the 2016-2017 academic year.