# Overview

## Changes from 119f054cfd590017fba1f90838b42c5e97759681 to current

```---
title: Lecture Notes - AIS2204 Maskinsyn
categories: Module
---

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

**Note** The lecture plan as posted at the start of semester is last
year's schedule.  There will not be any revolutionary changes, but
it will be reviewed and amended as we go along.

| # | Lecture Notes | Exercise  | Reading | Keywords |
| :- | :- | :- | :- | :- |  :- |
| 1 | [Introduction]() | [IntroductionLab]() | Ma 2004:Ch 1 (Ch 2.1 and 2.3)  | Quick examples - software installation |
| 2 | N/A  | [3D Modelling]() | Ma 2004:Ch 2, App A (SZ 2) | 3D modelling, motion |
| 3 | N/A  | [3D Objects in Python]() | Tutorials |
| 4 | N/A  | [3D Modelling II]() | | More mathematics - quaternions? |
# Chapter 1-3. Introduction; 3D geometry and projections

## Learning Objectives
**Dates** 21, 24, 28, and 31 August, and 4 and 7 September

+ 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 Notes | Reading | Keywords | Status |
|---|---------------|-------------------|-----------------------------|-----|
| 1 | [Introduction]()         | Ma 2004:Ch 1 (Ch 2.1 and 2.3) | Practical matters. Software installation. Recap of linear algebra. | OK |
| 2 | [3D Modelling]()         | Ma 2004:Ch 2, App A (SZ 2)   | 3D modelling, motion | OK |
| 3 | [3D Objects in Python]() | Tutorials                    | Homogeneous co-ordinates.  General Rotations. 3D Transformations in Python | OK |
| 4 | [Image Formation]()    | Ma 2004:Ch 3-3.3.1 (SZ 6) | (self-study) projection, lens/camera | |
| 5 | [Camera Calibration]() | Ma 2004:Ch 3.3-3.3.3 | (self-study) Calibration, Radial Distortion etc. |
| 6 | [Three-week Recap]()   | Ma 2004:Ch 1-3 | 3D Motion and 2D Projections |  To be adapted to class need|
| 7 | Recap: [Camera Calibration]() | Ma 2004:Ch 3 | | Many students needed more time to get the calibration to work.  |

# Chapter 3. Image Formation (two weeks)
**Note** It could have been useful to do a session on Theorem 2.8, training proof

| # | 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](https://docs.opencv.org/master/dc/dbb/tutorial_py_calibration.html) | Radial Distortion, Tangential Distortion |
| 8 | [Programming with OpenCV]() | ?? | videos, **TBD** |
# Chapter 4. Feature Tracking

+ Session 5-8
- Projection from 3D to 2D image
- Calibrate camera
We need to interleave this with material from later blocks to have
project tracker run over midterm.
[Study Technique]() may be a good candidate.

# Chapter 4. Feature Tracking (two weeks)
| # | Topic  | Reading | Keywords | Status |
| -: | :- |  :- |  :- |  :- |
| 8 (14 Sep) | [Image Filters]() | Convolution.  Filters.  Blurring. | |
| 9 | [Corner Detection]() | Ma 2004:Ch 4.3, 4.A (SZ 4) | Calculate Gradient.  Harris Feature Detector. | |
| 10 (21 Sep) | [Tracking Features]() |  Ma 2004:Ch 4-4.2 | Tracking of Features. Tracking of Edges. | |
| 11 | [SIFT]() | | Feature Matching.  Feature Descriptor. | |
| 12 (28 Sep) | [Edges]() | Ma 2004:Ch 4.4 | Canny, connected components, line fitting | |
| 13 | [Colour]() Models |
| 14 (5 Oct) | [Relative Pose]() | Ma 2004:Ch 5.1 | Triangulation. Relative Pose. Essential Matrix. |
| 15  | [Project Tracker]() | | [Multiscale Detection]() | |
| 16 (12 Oct) | *Self-Study* | Continue with [Tracking Features]() | - | - |
| 17 | Recap      | | Status, review, repetition | |

**Keywords** Signal Processing, 2D
# Chapter 5. Projective Reconstruction

| # | 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]() |
| # | Topic  | Reading | Keywords | Status |
|---|---------------|-------------------|-----------------------------| -: |
| 18 (19 Oct) | [Eight-point algorithm]() | Ma 2004:Ch 5.2 | Calculate Essential Matrix | OK |
| 19 | [Study Technique]() | Ma 2004:Ch 5.1 | Proof reading. | OK |
| 20 (26 Oct) | [Planar Scenes]()| Ma 2004:Ch 5.3 | |
| 21 (30 Oct) | [Epipolar Geometry]()| Ma 2004:Ch 5.1-3 | |
| 22 | self study [3D Reconstruction]()  | Ma 2004:Ch 5.1-2 |  Continuous on 18 [Eight-point algorithm]() using real image data |  OK |

# Chapter X.  Machine Learning

+ 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.
| #  | Topic         | Reading | Keywords |
|----|---------------|-------------------|-----------------------------|
| 23-24 | [Neural Networks]() | Szeliski 2022 Chapter 5 | Training. Testing |
| 25 | [Statistics]() |  | Evaluation, Standard Deviation |
| 26 | [Object Detection]() | Szeliski 2022 Chapter 6 (6.3 in particular) | Object Detection |
| 27 | [Regression]() | | |
| 28 | [Distorted Space]() + Recap  | Ma 2004:Ch 6.1-2 | Questions; Answers; module evalutaiton |

# 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
# Other Material.

## 2-3
+ [Overview of Python Demoes](Python/Overview)
+ The material is under constant review.
+ Any feedback is welcome.
+ Existing notes for [Review]()

1. Ma 2004 Chapter 11.3.
# Old Material.

# Project 3.  Euclidean Reconstruction
| # | Topic  | Reading | Keywords |
|---|---------------|-------------------|-----------------------------|
| 24/2021 | [Stratified Reconstruction]() | Ma 2005:Ch 6.3-4  | |
| 25/2021 | [Partial Scene Information]() | Ma 2005:Ch 6.5  | |
| 26/2021 | [Real World Reconstruction]() | Ma 2004:Ch 11 |  |
| 27/2021 | [Continuous Motion]() | Ma 2004:Ch 5.4 | |

1. Ma 2004 Chapter 10.  Partial Scene Knowledge
- This is referenced as a building block in Chapter 11.
1. Ma 2004 Chapter 11.4.
1. Ma 2004 Chapter 11.5.  **Keywords** texture, visualisation

# 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.
```