|Instructor:||Prof. Chuck Stewart|
|Course Hours:||Mon, Thu 10:00 - 11:30|
|Class Location:||Low 3045|
|Office Location:||MRC 330B|
|Office Hours :||Mon, Thu after class; Tue 1-3; by appointment; drop-in|
Homework will involve solving mathematical problems, developing algorithms, and writing programs. The mixture of these will vary between assignments, although the programming aspect will tend to be the most important.
Programming can be done in Matlab with the Image Processing Toolkit or in C or C++, using OpenCV or VXL. If you use one of the latter, you will need to include some way of examining images and other results. My strong suggestion for this course is use of Matlab. If you continue with computer vision beyond this course, especially for working in industry, you should eventually transition to writing in C, C++ or Java.
Programming can be done in Matlab or in C or C++. My strong recommendation is Matlab, at least for this course. If you choose to use C or C++, you will want to make use of either OpenCV or VXL. The former is widely used. The latter is used in my lab, mostly for historical reasons, and it powerful and flexible, if a bit daunting.
Most students are likely to want to use Matlab, together with the
Image Processing Toolkit. Students who don't already have these on
their computer may sign up and download through
RPI's campus system.
Below you will find a selection of on-line resources for
learning Matlab. Often, however, the simplest thing to do is type a
query into a search engine (for example, for homework 1, try to learn
Many books on computer vision have been published over the years. We will be using the on-line textbook, Computer Vision: Algorithms and Applications , which Dr. Richard Szeliski of Microsoft Research has just finished writing. See his website for links to other computer vision courses taught throughout the country.
Here are several other books that students might find useful: