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---
title: Lecture Notes - AIS2204 Maskinsyn
categories: Module
---
# 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 Calibration]() | Ma 2004:Ch 3.3-3.4 | Calibration, Radial Distortion etc. |
| 7 | [More Camera Mathematics]() | [Calibration in OpenCV](https://docs.opencv.org/master/dc/dbb/tutorial_py_calibration.html) | Radial Distortion, Tangential Distortion |
| 8 | Seminar: Applications | ?? | **TBD** |
| 8 | Tentative Seminar: Applications | ?? | **TBC** - we may decide to move on to feature tracking |
# Chapter 4. Feature Tracking (two weeks)
| # | 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]() |
+ OpenCV/Python Tutorial
- Background: [Understanding Features](https://docs.opencv.org/master/df/d54/tutorial_py_features_meaning.html)
- [Harris Corner Detection](https://docs.opencv.org/master/dc/d0d/tutorial_py_features_harris.html)
- Overview
[Feature Detection and Description](https://docs.opencv.org/master/db/d27/tutorial_py_table_of_contents_feature2d.html)
+ Ma 2004 Chapter 11.1-2.
# Chapter 5. Projective Reconstruction (two weeks)
**Keywords** 3D, projection
## 2-1
+ Ma 2004 Chapter 5
1. The Epipolar plain
1. 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
1. 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.