CSCI1430
Computer Vision
Spring 2026
How can we program computers to understand the visual world? This course treats vision as inference from noisy and uncertain data and emphasizes probabilistic and statistical approaches. Topics may include perception of 3D scene structure from stereo, motion, and shading; segmentation and grouping; texture analysis; learning, object recognition; tracking and motion estimation. Strongly recommended: basic linear algebra, calculus, and probability.
Instructor(s): | |
Meets: | TTh 9am-10:20am Location TBD |
Exam: | If an exam is scheduled for the final exam period, it will be held: |
Max Seats: | 150 |
CRN: | 26703 |