Instructor: Vassilis Athitsos
This course introduces students to basic concepts and techniques in computer vision. The topics covered include image filters, edge detection, feature extraction, object detection, object recognition, tracking, gesture recognition, image formation and camera models, 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. Matlab will be the primary programming language/environment used in the programming assignments. Students should ensure they have access to Matlab, including Matlab's image processing toolbox.
Grading will be based on weekly programming assignments and a final programming project. Class lectures involve introducing and explaining computer vision concepts, and writing Matlab code illustrating how those concepts can be implemented and applied to specific examples. Programming assignments expand upon the code developed in lectures, so as to improve accuracy, efficiency, and/or generality.
Course web page:
Lecture times: Tuesday and Thursday, 12:30pm-1:50pm
Classroom: NH 229