CSCI1430
Computer Vision
Fall 2024
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 Permission Required
| Instructor(s): | |
| Home Page: | http://cs.brown.edu/courses/csci1430/ |
| Meets: | TTh 9am-10:20am in MacMillan Hall 115 (9/4 to 9/11)
TTh 9am-10:20am in Barus & Holley 166 (9/12 to 12/21) |
| Exam: | No final exam has been scheduled for this course by the department through the registrar's office. Please consult syllabus or contact instructor. If an exam were to have scheduled, it would have been held: |
| Max Seats: | 95 Full |
| CRN: | 18540 |
Spring 2025
As above
| Instructor(s): | |
| Home Page: | http://cs.brown.edu/courses/csci1430/ |
| Meets: | TTh 9am-10:20am in MacMillan Hall 115 |
| Exam: | If an exam is scheduled for the final exam period, it will be held: |
| Max Seats: | 160 Full |
| CRN: | 26480 |
