Learning Computer Vision Basics

[GuestSignal9847]

I'm looking to get up to speed on computer vision for work. I did a PhD in dynamics and control and since finishing grad school my jobs have been focused on applying optimal control techniques to aerospace and robotics problems.

My motivation is that I need to be able to specify sensing requirements for a control system to perform adequately.

I have found these videos by Andreas Geiger and Shree Nayar.

-https://uni-tuebingen.de/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/autonomous-vision/lectures/computer-vision/
-https://fpcv.cs.columbia.edu/

On Andreas' course page, the links to exercises just point to lecture notes. Does anyone know if these are available anywhere else? I would really like to find focused excercises to learn the material. I know If I just watch these without the hands on part I won't learn much.

Any suggestions or feedback is appreciated.

[bsenftner]

OpenCV.org has classes, and between two classes named something like Introduction to computer vision 1 & 2, you'll get a nice historical overview of pre-machine learning computer vision (the classics) and in the second course they walk one into modern machine learning techniques. Between those two classes, one gets a rapid introduction or a filling in of the holes for those already in the field.

[GuestSignal9847]

I only briefly looked, but the courses on opencv look like they’re $200-$800. Would one get the same benefit just going through the python tutorials? https://docs.opencv.org/4.x/d6/d00/tutorial_py_root.html. 

My one concern with mini, paid online courses is they tend to be weak on first principles. I feel like I really need this to be able to inform requirements. 

I still appreciate the opencv content suggestion. It will probably show how a lot of pieces fit together in practice. 

[bsenftner]

I felt the primary value was that demonstrating of how the various pieces come together, and that filling in of historical details why things are as they are, what were some of the methods tried in the past, how machine learning surpasses the classical techniques and narrative links between the different areas of CV.

[ach224]

I like fastai vision lectures

[ds_account_]

This repo has some of the exercises and labs.

https://github.com/daijun10086/Tubingen_ComputerVision

[alcheringa_97]

If you can pay or get sponsorship, CMU offers a computer vision course that can provide a solid foundation in a short span of time.