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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. Recap of linear algebra.
2 3D Modelling Ma 2004:Ch 2, App A (SZ 2) 3D modelling, motion
3 3D Objects in Python Tutorials Homogeneous co-ordinates. General Rotations. 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 3.3-3.3.3 Calibration, Radial Distortion etc.
7 More Camera Mathematics Ma 2004:Ch 3.3-3.4 Radial Distortion, Tangential Distortion

Chapter 4. Feature Tracking (three weeks)

# Topic Reading Keywords
new Signal Processing Convolution. Filters. Blurring.
8 Corner Detection Ma 2004:Ch 4.3, 4.A (SZ 4) Calculate Gradient. Harris Feature Detector.
9 Corner Detection continued new Multi-Scale Detection
10 Tracking Features Ma 2004:Ch 4-4.2 Tracking of Features. Tracking of Edges.
11 Edges Ma 2004:Ch 4.4
12 Self-Study Continue with Tracking Features
13 Standup Continue with Tracking Features
15 Tracking Features 2 TODO Long project?
16 SIFT Feature Matching. Feature Descriptor.

Note Session 12 was planned Self-Study due to staff seminar. Session 13-14 became self-study because of sick leave, and negligible progress was made this week.

Note for next year We should have had one session on blurring filters and similar techniques from image processing before starting on Corner Detection (Session 8). This would have made the introduction of signal differentiation smoother.

Chapter 5-6 and 11. Projective Reconstruction (many weeks)

This plan is tentative.

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


# 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.
  2. Ma 2004 Chapter 11.4.
  3. Ma 2004 Chapter 11.5. Keywords texture, visualisation