Computer vision is the science and technology of machines that can see. As a science, the goal of computer vision is to understand the computational processes required for a machine to come to an understanding of the content of a set of images. The data here may be a single snapshot, a video sequence, or a set of images from different viewpoints or provided by medical scanners.
The computer vision focus introduces students to the study of vision from a computational point of view. That is, we attempt to clearly define computational problems for various steps of the overall process, and then show how these problems can be tackled with appropriate algorithms.
Students who wish to pursue computer vision should have an understanding of linear algebra and calculus of several variables. Moreover, they should be solid programmers and have a good understanding of data structures and algorithm design. These basic tools are required in order to first pose computational vision problems, and then develop and test algorithms for their solution.
- MAT235Y1/MAT237Y1/MAT257Y1, CSC320H1, CSC350H1, CSC411H1, CSC420H1
- 0.5 FCE from the following: CSC418H1, CSC412H1, CSC2503H (Note: students must petition to take this course.)
Suggested Related Course:
The following are examples of topics and courses that fit naturally with a study of computational vision. The list is meant to be illustrative of the range of cognate topics, but is not necessarily complete. The ordering is alphabetical and not indicative of importance. Note: there are prerequisites for many of these courses that we do not list here.
APM462H1, COG250Y1, CSC384H, CSC485H1, CSC486H1, PHL232H1, PHY385H1, PSL440Y1, PSY270H1, PSY280H1, STA257H1/STA261H1