Lentera 
Lecture 1
What is computer vision?
Vision as inverse graphics, Why seeing is hard, A short history, Applications and course map
Computer
Vision
Twelve lectures on how computers understand pictures.
You looked at these flowers for less than a second, and you already know more about them than any computer program.
This is a free course for teachers of computer vision and for students who want to learn it. Every lecture has slides to present and a guide for the teacher: what to say on each slide, how much time to spend, what to ask the class, and exercises with answers.
The course starts with how a camera turns light into numbers. It ends with models that understand both pictures and words. Students need some basic maths (vectors, matrices, derivatives) and some Python.
How to teach with these materials
Dalam Bahasa Indonesia: materi kuliah computer vision, ringkasan dan daftar pertemuan.
Part I — Images and classical vision
Lecture 2
Image formation
Pinhole camera and perspective projection, Lenses, focus and field of view, Light, colour and sensors, Sampling, quantization and colour spaces
Lecture 3
Images as signals
In preparation
Lecture 4
Linear filtering and edges
In preparation
Lecture 5
Pyramids and scale
In preparation
Part II — Learning to see
Lecture 6
From classifiers to neural networks
In preparation
Lecture 7
Convolutional networks and transformers
In preparation
Lecture 8
Features and matching
In preparation
Lecture 9
Object recognition and detection
In preparation
Lecture 10
Image segmentation
In preparation
Lecture 11
Video, motion and temporal models
In preparation
Lecture 12
Vision and language
In preparation
Lecture photographs from Wikimedia Commons; authors and licenses are on the credits page.