Course Detail
Units:
3.0
Course Components:
Lecture
Enrollment Information
Enrollment Requirement:
Prerequisites: 'C-' or better in(CS 3505 AND(MATH2270 OR 2271 OR 2250)) AND Foundational Courses complete AND (Major OR Minor in Kahlert School of Computing OR ECE)
Description
Introduction to fundamental problems of Computer Vision and main concepts and techniques to solve those. Topics in this class include camera pose estimation, 3D reconstruction, feature detectors and descriptors, object recognition using vocabulary tree, probabilistic graphical models, segmentation, stereo matching, graph cuts, belief propagation, and a brief introduction to deep neural networks.