|Meeting Time:||T hr: MW 3:00-4:20|
|Exam Group:||10: 17-MAY-2019 Exam Time: 09:00:00 AM|
|Offered this year?||Yes|
|When Offered?||Most years|
How can computers understand the visual world of humans? This course treats vision as a process of 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; image filtering, smoothing, edge detection; segmentation and grouping; texture analysis; learning, recognition and search; tracking and motion estimation. Strongly recommended: basic linear algebra, basic calculus and exposure to probability.