Theory + Math for Computer vision + Robotics

CS

https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-042j-mathematics-for-computer-science-fall-2010/readings/MIT6_042JF10_notes.pdf
http://www.cse.buffalo.edu/~hungngo/teaching.html
https://www.cs.princeton.edu/courses/archive/fall06/cos341/handouts/mathcs.pdf

CV

http://www.robots.ox.ac.uk/~vgg/hzbook/
http://stackoverflow.com/questions/824679/how-can-i-learn-the-math-necessary-for-working-with-computer-vision

As for learning the math, after taking a introductory linear algebra class, I think getting exposure to linear algebra in the computer vision context should be good enough. Also getting a good foundation in graphics (OpenGL) should be helpful too.

Our university used this book:

• Computer Vision - A Modern Approach

As a beginner I liked these books:

• An Invitation to 3-D Vision - From Images to Geometric Models
• An Introduction to 3D Computer Vision Techniques and Algorithms

• Multiple View Geometry in Computer Vision by Hartley and Zisserman

Wikipedia has been a great resource, here are some computer vision topics. More links here andhere.

Also IEEE, ACM, and your university have access to lots of research papers. Finding old computer vision lectures like this course at UNC have also been useful.

https://sites.google.com/site/mostafasibrahim/research/articles/how-to-start#TOC-Machine-Learning

http://www.cse.iitd.ernet.in/~suban/vision/

Robotics

https://en.wikibooks.org/wiki/Category:Robotics_(book)  all information

- calculus
- ordinary differential equations
- linear algebra (you need a very strong background in linear algebra)
- numerical methods (not numerical analysis)

- dynamics
- kinematics
- linear controls

- statistics, probability, and Bayesian inference 
- nonlinear/adaptive controls
- optimal controls
- advanced linear algebra
- numerical analysis
- advanced numerical methods/scientific computing

Mechanics is about:

• how forces are transferred between the different parts of a construction.
• where the center of gravity lies.
• friction
• position, speed, acceleration
• Newton's laws
• inertia
• material properties

Electronics is about:

• Electronic Components
• Analog Circuits
• Digital Logic
• MicroControllers

Computer programming is about:

• Control structures (sequence, selection, iteration)
• Data types (constants, variables, integer, real, string,...)
• Algorithms
• Hardware control (setting and reading registers, interrupts,...)
• logic

Artificial Intelligence (in Robotics) is about:

• Finding the shortest way between 2,3 (or more) points
• Dealing with obstacles
• Handling new situations (machine learning)