Computer Vision
3.0
creditsAverage Course Rating
This course provides an overview of fundamental methods in computer vision from a computational perspective. Methods studied include: camera systems and their modelling, computation of 3¬D geometry from binocular stereo, motion, and photometric stereo, and object recognition, image segmentation, and activity analysis. Elements of machine learning and deep learning are also included. Required course background: Intro to Programming, Linear Algebra & prob/stats