travisddavies / computer_vision_notes

My lecture notes for Computer Vision at The University of Melbourne.

Computer Vision Notes

These are my notes for Computer Vision, COMP90086 at the University of Melbourne. Given the rather lean lecture slides, I've tried to add more detail.

Note

These notes should be read via Obsidian. The latex and embedded media does not render very well via GitHub.

In the Works

• Additional exercises off the internet

To get the notes, simply use the following:

git clone [email protected]:travisddavies/computer_vision_notes.git

Table Of Contents

1. Imaging Basics
2. Spatial Filtering
3. Frequency Filtering
4. Light, Colour & Shadow
5. Edge Detection
6. Convolutional Neural Networks I
7. Convolutional Neural Networks II
8. Deep Learning I
9. Deep Learning II
10. Features
11. Feature Matching
12. Depth and Stereo
13. Multiview Depth
14. Texture
15. Shape
16. Image Generation
17. Generative Adversarial Networks (GANs)
18. Image Segmentation I
19. Image Segmentation II
20. Object Detection I
21. Object Detection II