CSCI0453A-S20
Computer Vision
Computer Vision
The goal of computer vision is to extract information from digital images and movies. Topics covered in this course include algorithms for edge and motion detection, stereo vision, object recognition, and recovering structure from motion. A range of mathematical techniques will be used to model problems and algorithms. Students will implement, test, and evaluate several computer vision techniques, and will gain experience with analyzing real, noise-contaminated image data. (CSCI 0202 and MATH 0200) 3 hrs. lect./lab
The goal of computer vision is to extract information from digital images and movies. Topics covered in this course include algorithms for edge and motion detection, stereo vision, object recognition, and recovering structure from motion. A range of mathematical techniques will be used to model problems and algorithms. Students will implement, test, and evaluate several computer vision techniques, and will gain experience with analyzing real, noise-contaminated image data. (CSCI 0202 and MATH 0200) 3 hrs. lect./lab
- Term:
- Spring 2020
- Location:
- 75 Shannon Street 224(75SHS 224)
- Schedule:
- 9:30am-10:45am on Tuesday, Thursday (Feb 10, 2020 to May 11, 2020)
- Type:
- Lecture
- Instructors:
- Jason Grant
- Subject:
- Computer Science
- Department:
- Computer Science
- Division:
- Natural Sciences
- Requirements Fulfilled:
- DED
- Levels:
- Undergraduate
- Availability:
- View availability, prerequisites, and other requirements.
- Course Reference Number (CRN):
- 22222
- Subject Code:
- CSCI
- Course Number:
- 0453
- Section Identifier:
- A