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Lecture Notes - AIS2204 Maskinsyn
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.
Chapter 1-2. Introduction and 3D Modelling (two weeks)
Dates
# | 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
Chapter 4. Feature Tracking (three weeks)
(Last year’s session numbers in parentheses.)
# | 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. | OK |
11 (new) | Project Tracker | Multiscale Detection | OK | |
12 (16) | SIFT | Feature Matching. Feature Descriptor. | OK | |
13-14 | Self-Study | Continue with Tracking Features | - | - |
15 (11) | Recap | Status, review, repetition | ||
16 (11) | Edges | Ma 2004:Ch 4.4 | Canny, connected components, line fitting |
Chapter 5. Projective Reconstruction (two weeks ?)
# | 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 | 3D Reconstruction | Ma 2004:Ch 5.1-2 | |
21 | Planar Scenes | Ma 2004:Ch 5.3 | |
22 | Epipolar Geometry | Ma 2004:Ch 5.1-3 |
- Study Technique should may be needed earlier. We introduced some fragments of this in 2022, but should possibly do more of it.
- Relative Pose is a little messy. It serves covers two things.
- triangulation is poorly covered in the textbook and the notes, but the students need a recap from basic calculus
- the essential matrix is preparation for the next session.
- Generally, the preliminary steps of the exploratory exercises should have been premade, to save time for the students. We have made some improvements in 2022, but we should do more.
- Algorithm implementation is difficult and require sample solutions. Some have been added in 2022, but may have to be incorporated earlier in the course.
- We need more examples with complete calculations
New. Machine Learning
# | Topic | Reading | Keywords |
---|---|---|---|
23-24 | Neural Networks | Szeliski 2022 Chapter 5 | Training. Testing |
25 | Statistics | Evaluation, Standard Deviation | |
26 | Regression |
- We should go further into Object Recognition next year
Last Week. Summary and Miscellanea
# | Topic | Reading | Keywords |
---|---|---|---|
27 (23) | Distorted Space | Ma 2004:Ch 6.1-2 | |
28 | Recap | The Entire Syllabus | Questions & Answers |
Other Material.
Old Material.
# | 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 |
- Ma 2004 Chapter 10. Partial Scene Knowledge
- This is referenced as a building block in Chapter 11.
- Ma 2004 Chapter 11.4.
- Ma 2004 Chapter 11.5. Keywords texture, visualisation