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Lecture Notes - AIS2204 Maskinsyn

Introduction (two weeks?)

# Topic Reading Keywords
1 Introduction Ma 2004:Ch 1 Quick examples - software installation
2 3D Modelling Ma 2004:Ch 2, App A (SZ 2) 3D modelling, motion
3 3D Objects in Python Tutorials
4 3D Modelling II More mathematics - quaternions?
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

Learning Objectives

  • Session 1.
    • how to work with the subject
    • history, motivation, purpose
    • (debrief) basic linear algebra
  • Session 2-4. (3-4 sessions total)
    • Rotation, Translation
    • Exponential Form
    • Change of basis
    • Homogenous Co-ordinates
    • Mathematical properties
    • Mathematical and insrumental formulations
  • Session 5-7
    • Project from 3D to 2D image
    • Calibrate camera

Project 1. Feature Tracking (three 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 Tracking Features Ma 2004:Ch 4-4.2 Tracking of Features. Tracking of Edges.
2 Corner Detection in Python
4 Tracking Features in Python

Project 2. Projective Reconstruction (three weeks)

Keywords 3D, calibration, 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.

Project 4. Visualisation

Keywords texture, visualisation

  1. Ma 2004 Chapter 11.5.