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Lecture Notes - AIS2204 Maskinsyn

Chapter 1-2. Introduction and 3D Modelling (two weeks)

# Session Notes Reading Keywords
1 Introduction Ma 2004:Ch 1 (Ch 2.1 and 2.3) Practical matters. Software installation. Reap of linear algebra.
2 3D Modelling Ma 2004:Ch 2, App A (SZ 2) 3D modelling, motion
3 3D Objects in Python Tutorials 3D Transformations in Python
4 3D Modelling Part II Velocity transformations. Recap. Questions.

Chapter 3. Image Formation (two weeks)

# Topic Reading Keywords
5 Image Formation Ma 2004:Ch 3-3.3.1 (SZ 6) projection, lens/camera
6 Camera Mathematics Ma 2004:Ch 3.3-3.4 Calibration, Radial Distortion etc.
7 Distortion in Practice Calibration in OpenCV Radial Distortion, Tangential Distortion
8 Programming with OpenCV ?? videos, TBD
  • Session 5-8
    • Projection from 3D to 2D image
    • Calibrate camera

Chapter 4. Feature Tracking (two weeks)

Keywords Signal Processing, 2D

# Topic Reading Keywords
1 Corner Detection Ma 2004:Ch 4.3, 4.A (SZ 4) Calculate Gradient. Harris Feature Detector.
2 Corner Detection in Python
3 Tracking Features Ma 2004:Ch 4-4.2 Tracking of Features. Tracking of Edges.
4 Tracking Features in Python

Chapter 5. Projective Reconstruction (two weeks)

Keywords 3D, projection

2-1

  • Ma 2004 Chapter 5
  1. The Epipolar plain
  2. Eight-point algorithm

2-2

  1. Ma 2004 Chapter 5

2-3

  1. Ma 2004 Chapter 11.3.

Project 3. Euclidean Reconstruction

  1. Ma 2004 Chapter 10. Partial Scene Knowledge
  2. Ma 2004 Chapter 11.4.

Chapter 6. Reconstruction from two Uncalibrated views (two weeks)

Keywords 3D, calibration, projection

Chapter 11. System Architecture (one week?)

Visualisation (one week?)

Keywords texture, visualisation

  1. Ma 2004 Chapter 11.5.

Chapter 10. Partial Scene Knowledge (one week?)

This is referenced as a building block in Chapter 11.