Synopsis: We will read seminal research papers in computer vision and showcase some recent inventions and discoveries from the most important conferences in the field. The format will be alternating instructor and student presentations: I will give an introduction to a paper's general area, the background and the problem setting, then we'll read the paper as homework, and one student will present it in the following lecture. We will meet two hours a week - you will get credit for the third hour because of the amount of reading involved. This is a pass/fail course.
Prerequisites: CS4330 Computer Vision or another computer vision or image processing course, linear algebra, Matlab or C/C++, and an interest in computer vision applications. If you are unsure about the math that will be required to understand most of the methods, have a look at Gonzalez' and Woods' review of the essentials. That should suffice.
Meeting Times: TBD.