Spring 2021
Lectures: MWF 10:00am-10:50am
All lectures are conducted online, using Microsoft Teams.
Instructor: Vassilis Athitsos
This course introduces students to basic concepts and techniques in computer vision. The topics covered include moprhological operations, connected component analysis, image filters, edge detection, feature extraction, object detection, object recognition, tracking, gesture recognition, image formation and camera models, calibration, and stereo vision. A strong programming background is assumed, as well as familiarity with linear algebra (vector and matrix operations), and knowledge of basic probability theory and statistics. Prerequisites: Admitted into an Engineering Professional Program, and C or better in each of the following: Algorithms (CSE 3318), Probability (IE 3301), and Linear Algebra (CSE 3380 or MATH 3330).