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Lecture Notes - AIS2204 Maskinsyn
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)
(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 | new Lecture 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 |
- 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 ?)
# | 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 |
---|---|---|---|
23/2021 | Distorted Space | Ma 2004:Ch 6.1-2 |
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