Course Detail
Units:
3.0
Course Components:
Lecture
Enrollment Information
Enrollment Requirement:
Prerequisites: CS 3505 AND MATH 2270.
Description
Meets with CS 5320. Introduction to fundamental problems of 3D Computer Vision and main concepts and techniques to solve those. Discussion of analysis methodologies and techniques to extract and model 3D information acquired via passive or active sensors, including multiple cameras, range sensors, structured light and 3D from camera motion. Methodologies include camera calibration, epipolar and multi-view geometry, shape from shading, photometric stereo, optical flow, camera motion, silhouettes, and object tracking, implementation of image, processing and vision method in programming projects.