Computer Science CS 682 / 001
Meets Friday, 1:30 pm - 4:10 pm, in West 1008
Professor Zoran Duric.
About the Class The goal of computer vision is to compute properties of the three-dimensional world from digital images. Problems in this field include identifying the 3D shape of an environment, determining how things are moving, and recognizing familiar people and objects, all through analysis of images and video. This course provides an introduction to computer vision, including such topics as feature detection, image segmentation, motion estimation, 3D shape reconstruction, and object recognition.
- Algorithms and Data Structures
- Artificial Intelligence
- Linear algebra and calculus
- A good working knowledge of C/C++ or Java or Python programming
- Concise Computer Vision, Reinhard Klette, Springer, 2014,
required, Book website, see
- Computer and Machine Vision: Theory, Algorithms,
Practicalities, E.R. Davies, Academic Press, 2017, highly
recommended , A lot of well-explained algorithms with
- A practical introduction to computer vision with opencv, Kenneth
Dawson-Howe. John Wiley & Sons, 2014, recommended
OpenCV: projects will require
OpenCV. OpennCV is a C/C++ open source library with wrappers in
Java, Python and Matlab. I recommend the Python version.
Course Web Page CS 682: Computer Vision We will communicate through piazza. Slides, handouts, and assignments will be posted on the web page.
Grading Grading will be based on a combination of the following factors:
- Programming homeworks 40% (about every 2 weeks).
- A final group project 20%.
- A midterm 20%.
- A final 20%.
Honor Code The class enforces the GMU Honor Code, and to the more specific honor code policy special to the Department of Computer Science. You will be expected to adhere to this code and policy.
DisabilitiesIf you heve a documented learning disability or other condition which may affect academic performance, make sure this documentation is on file with the Office of Disability Services and come talk to me about accommodations.