Narrow Results

This paper provides a survey of the variety of computer vision [CV] and image processing [IP] courses being taught at institutions around the world. The survey shows that, in addition to classic survey courses in CV/IP, there are many focused and multidisciplinary courses being taught that reportedly improve both student and faculty interest in the topic. It also demonstrates that students can successfully undertake a variety of complex lab assignments. In addition, this paper includes a comparative review of current textbooks and supplemental texts appropriate for CV/IP courses.

This paper describes a course in image computation that is designed to follow and build up an established course in computer graphics. The course is centered on images: how they are generated, manipulated, matched and symbolically described. It builds on the student's knowledge of coordinate systems and the perspective projection pipeline. It covers image generation techniques not covered by the computer graphics course, most notably ray tracing. It introduces students to basic image processing concepts such as Fourier analysis and then to basic computer vision topics such as principal components analysis, edge detection and symbolic feature matching. The goal is to prepare students for advanced work in either computer vision or computer graphics.