Introduction
Computer vision is a field of artificial intelligence that enables computers and systems to derive meaningful information from digital images, videos and other visual inputs — and take actions or make recommendations based on that information. Computer vision works much the same as human vision, except humans have a head start. Human sight has the advantage of lifetimes of context to train how to tell objects apart, how far away they are, whether they are moving and whether there is something wrong in an image. Computer vision trains machines to perform these functions, but it has to do it in much less time with cameras, data and algorithms rather than retinas, optic nerves and a visual cortex.
Content
2D Vision
Geometric Image Formation
Digital Image Representation
Image Processing
Image Filtering
Domain Adaptation
3D Vision
Line Fitting
Single View Geometry
Two View Geometry
Multiple View Geometry
Optical Flow
Shape-From-X
High Level Vision
Other Resources
- Tom Dalling, Explaining Homogeneous Coordinates & Projective Geometry
- CS231A Course Notes 3: Epipolar Geometry
Acknowledgement
This part is mainly based on the ANU course COMP4528 in 2024.