Computer Science 670 - Computer Vision

People are able to infer the characteristics of a scene or object from an image of it. In this course, we will study what is involved in building artificial systems which try to infer such characteristics from an image. Topics include: Basics of image formation - the effect of geometry, viewpoint, lighting and albedo on image formation. Basic image operations such as filtering, convolution and correlation. Frequency representations of images. The importance of scale in images. Measurements of image properties such as color, texture, appearance and shape. Inference of motion and structure from moving objects and images. Detecting and recognizing objects in images. Statistical methods in computer vision. Prerequisite: Linear algebra, calculus, basic knowledge of probability, and an ability to program.

Open to Graduate Computer Science students only. PREREQUISITES ARE LINEAR ALGEBRA, CALCULUS 1 AND 2, MULTI-VARIATE CALCULUS OR PERMISSION OF INSTRUCTOR. STATS 515 OR PERMISSION OF INSTRUCTOR. ADVANCED UNDERGRADUATES WITH PERMISSION OF INSTRUCTOR. SEATS HELD FOR INCOMING STUDENT REGISTRATION. STUDENTS NEEDING INSTRUCTOR PERMISSION MUST REQUEST OVERRIDES VIA THE ON-LINE FORM: https://www.cics.umass.edu/overrides.