Provides a mathematical framework for describing three dimensional imaging and computer vision. Topics include 3-D coordinate transforms, image formation, camera calibration, reconstruction from two views, SIFT detection, hidden Markov models, Markov random fields, and "bag-of-words" visual description. Prerequisites: EE 4220 and MATH 2250.