Introduction to Computer Vision
Computer vision is an immense subject, more than any single tutorial can cover.
In the following tutorials I will cover the basics of computer vision in four parts,
each focused on need-to-know practical knowledge.
Part 1: Vision in Biology
Part 1 will talk about vision in biology, such as the human eye, vision in
insects, etc. By understanding how biology processes visual images, you may
then be able to apply what you learned towards your own creations. This will help you
turn the 'magic' into an understanding of how vision really works.
Part 2: Computer Image Processing
Part 2 will go into computer image processing. I will talk about how a camera
captures an image, how it is stored in a computer, and how you can do basic
alterations of an image. Basic machine vision tricks such as heuristics, thresholding,
and greyscaling will be covered.
Part 3: Computer Vision Algorithms
Part 3 covers the typical computer vision algorithms, where I talk about
how to do some higher level processing of what your robot sees. Edge detection,
blob counting, middle mass, image correlation, facial recognition, and stereo vision will be covered.
Part 4: Computer Vision Algorithms for Motion
Part 4 covers computer vision algorithms for motion.
Motion detection, tracking, optical flow, background subtraction, and feature tracking will be explained.
There is also a problem set to test you on what you have learned in this computer vision tutorial series.
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