- Srinath Sridhar (fall '21) | James Tompkin (spring '22)
- Course Home Page:
|Meeting Time:||I hr: T,Th 10:30-11:50|
|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.
Prerequisites: CSCI 0160, 0180, or 0190