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

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

**Dates** 25-26 August + 1-2 September


| # | 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 | [3D Modelling Part II]() |                              | Velocity transformations.  Recap.  Questions. |  To be adapted to class |

# Chapter 3. Image Formation (two weeks)

| # | Topic  | Reading | Keywords | Status |
|---|---------------|-------------------|-----------------------------|------|
| 5 | [Image Formation]()    | Ma 2004:Ch 3-3.3.1 (SZ 6) | projection, lens/camera | OK |
| 6 | [Camera Calibration]() | Ma 2004:Ch 3.3-3.3.3 | Calibration, Radial Distortion etc. | OK |
| 7 | [More Camera Mathematics]() | Ma 2004:Ch 3.3-3.4 | Radial Distortion, Tangential Distortion | OK |

**Dates** 8-9 and 15 September

# Chapter 4. Feature Tracking (three weeks)

| # | Topic  | Reading | Keywords | Status |
|---|---------------|-------------------|-----------------------------|----|
| 8 (new) | [Image Filters]() | | Convolution.  Filters.  Blurring. | OK |
| 9 (8-9) | [Corner Detection]() | Ma 2004:Ch 4.3, 4.A (SZ 4) | Calculate Gradient.  Harris Feature Detector. | OK |
| 10 | [Tracking Features]() |  Ma 2004:Ch 4-4.2 | Tracking of Features. Tracking of Edges. |
| 11 (new)  | [Project Tracker]() | | **new** Lecture [Multiscale Detection]() | OK |
| 12 (16) | [SIFT]() | | Feature Matching.  Feature Descriptor. | OK |
| 13-14 | *Self-Study* | Continue with [Tracking Features]() | - |
| 15 (11) | [Edges]() | Ma 2004:Ch 4.4 | Recap.  Complete Project| TODO |

+ 8 - 16 September
+ 9-12 - 22-23 and 29-30 September
+ 13-14 - 6-7 October - staff seminar - self-managed work only
+ 15-16 - 13-14 October - midterm - regular teaching

# Chapter 5.  Projective Reconstruction (two weeks ?)

This plan is tentative and may be shortened as well as rearranged.
If necessary, Session 16 will be a recap of past material, particularly
the project, and the rest of the program shifted one session.
We will not know this until Session 15.

| # | Topic  | Reading | Keywords |
|---|---------------|-------------------|-----------------------------|
| 16 | [Relative Pose]() | Ma 2004:Ch 5.1 | Triangulation. Relative Pose. Essential Matrix. |
| 17 | [Eight-point algorithm]() | Ma 2004:Ch 5.2 | Calculate Essential Matrix |
| 18 | [Study Technique]() | Ma 2004:Ch 5.1 | Proof reading. |
| 19 | [Synthetic Experiment]()  | Ma 2004:Ch 5.1-2 |  |
| 20 | [Planar Scenes]()| Ma 2004:Ch 5.3 | |
| 22 | [Epipolar Geometry]()| Ma 2004:Ch 5.1-3 | |

*Notes from last year*

1.  [Synthetic Experiment]() should be merged into 
    [Eight-point algorithm]()
2.  [Study Technique]() should probably be done earlier in the semester
3.  3D modelling took a lot of time.  Many did not realise that they 
    needed to find triangles.
    Rectangles mixed with triangles caused problems.
4.  Generally, the preliminary steps of the exploratory exercises should have been
    premade, to save time for the students.
5.  Algorithm implementation is difficult and require sample solutions

# New.  Machine Learning

TBC

# Chapter 6 and 11.  Projective Reconstruction (many weeks)

This will be shortened and probably based on different sources.

| # | Topic  | Reading | Keywords |
|---|---------------|-------------------|-----------------------------|
| 23 | [Distorted Space]()  | Ma 2004:Ch 6.1-2 |  |
| 24 | [Stratified Reconstruction]() | Ma 2005:Ch 6.3-4  | |
| 25 | [Partial Scene Information]() | Ma 2005:Ch 6.5  | |
| 26 | [Real World Reconstruction]() | Ma 2004:Ch 11 |  |

*Notes from last year*

1. We can skip [Stratified Reconstruction]()
   and [Partial Scene Information]() 
2. [Distorted Space]()  may be interesting as an introduction to
   inner product spaces.
3. What can we make out of [Real World Reconstruction]()?


# Closure/Tentative

| # | Topic  | Reading | Keywords |
|---|---------------|-------------------|-----------------------------|
| 27 | [Continuous Motion]() | Ma 2004:Ch 5.4 | |
| 28 | Tentative Seminar: Applications | TBA | **TBC** - we may decide to move on to feature tracking |

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