Course Detail
Units:
3.0
Course Components:
Lecture
Enrollment Information
Enrollment Requirement:
Prerequisites: CS 3505 AND MATH 2270.
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.