3D Computer Vision | Lecture 4 (Part 1): Robust homography estimation

Here's the video lectures of CS4277/CS5477 3D Computer Vision taught at the Department of Computer Science, National University of Singapore (NUS).

This is an introductory course on 3D Computer Vision which was recorded for online learning at NUS due to COVID-19. The topics covered include:

Lecture 1: 2D and 1D projective geometry
Lecture 2: Rigid body motion and 3D projective geometry
Lecture 3: Circular points and Absolute conic
Lecture 4: Robust homography estimation
Lecture 5: Camera models and calibration
Lecture 6: Single view metrology
Lecture 7: The fundamental and essential matrices
Lecture 8: Absolute pose estimation from points or lines
Lecture 9: Three-view geometry from points and/or lines
Lecture 10: Structure-from-Motion (SfM) and bundle adjustment
Lecture 11: Two-view and multi-view stereo
Lecture 12: Generalized cameras
Lecture 13: Auto-Calibration

Disclaimer: This video lecture is provided freely for your reference. The lecturer and NUS are not responsible for anything expressed herein.

[trolleyproblem]

That data normalization is interesting.
Can you give some reference or more details?