The goal of computer vision is to compute properties of the three-dimensional world from digital images. Problems in this field include reconstructing the 3D shape of an environment, determining how things are moving, and recognizing people and objects and their activities, all through analysis of images and videos. This course will provide an introduction to computer vision, including such topics as image formation, feature detection, motion estimation, image mosaics, 3D shape reconstruction, and object recognition. Applications of these techniques include building 3D maps, creating virtual characters, organizing photo and video databases, human computer interaction, video surveillance, and automatic vehicle navigation. This is a project-based course, in which you will implement several computer vision algorithms and do a final project on a research topic of your choice. Prerequisites This course will be self-contained; students do not need to have computer vision background. This course will assume a reasonable knowledge of linear algebra. The programming assignments will be given in Matlab and C/C++, so a familiarity with these languages is desirable, though not essential. Please send me email or speak to me if you are unsure of whether you can take the course. Textbook |
