Computer Vision: Epipolar Geometry & Stereo Basics (Di, 13.01.2015)

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00:00:00
Lecture 17: Epipolar Geometry & Stereo Basics
00:00:16
Announcements: Exam Dates
00:03:42
Announcements: Seminar in the summer semester
00:07:07
Course Outline
00:08:25
Topics of This Lecture
00:09:09
Geometric vision
00:09:44
Visual Cues
00:14:05
Our Goal: Recovery of 3D Structure
00:15:52
To Illustrate This Point...
00:17:43
Stereo Vision
00:18:51
What Is Stereo Vision?
00:24:34
Application of Stereo: Robotic Exploration
00:27:34
Topics of This Lecture
00:28:02
Depth with Stereo: Basic Idea
00:29:46
Camera Calibration
00:33:00
Geometry for a Simple Stereo System
00:47:57
Depth From Disparity
00:48:53
General Case With Calibrated Cameras
00:49:58
Stereo Correspondence Constraints
00:54:06
Epipolar Geometry
00:57:02
Epipolar Geometry: Terms
00:58:17
Epipolar Constraint
00:59:38
Example
01:01:42
Example: Converging Cameras
01:02:34
Example: Motion Parallel With Image Plane
01:02:52
Example: Forward Motion
01:04:11
Let's Formalize This!
01:04:53
Stereo Geometry With Calibrated Cameras
01:05:56
Rotation Matrix
01:07:32
3D Rigid Transformation
01:08:07
Stereo Geometry With Calibrated Cameras
01:08:26
Excursion: Cross Product
01:09:23
From Geometry to Algebra
01:12:40
Matrix Form of Cross Product
01:14:58
From Geometry to Algebra
01:15:04
Essential Matrix
01:17:42
Essential Matrix and Epipolar Lines
01:21:29
Essential Matrix: Properties
01:21:39
Essential Matrix Example: Parallel Cameras
01:25:03
More General Case
01:25:13
Stereo Image Rectification
01:26:25
Stereo Image Rectification: Example
01:27:31
Topics of This Lecture
01:28:24
References and Further Reading