This assignment uses images taken in class *31 Jan 2018*. They may be downloaded
from Isidore resources (`CV2018-01-31.zip`

).

Submit HTML documentation and MATLAB files on Isidore.

Do **not** include a copy of `rvctools`

or the Bouguet calibration toolkit in your submission.

- Using images 15:20 from
*31 Jan 2018*, run a camera calibration. Follow the steps in this example from the Camera Calibration Toolbox for Matlab^{®}by Jean-Yves Bouguet. Compare the focal lengths to that obtained in Assignment 2.Do not submit a copy of the calibration toolbox. I do not need 7 more copies of the toolbox. Just submit the published MATLAB summary using

`calib_publish.m`

. - Use the Computer Vision calibration toolkit with the same 15:20 checkerboard images from
*31 Jan 2018*. Document the instrinsic calibration matrix and intrinsic parameters for the camera. Compare the focal lengths to those obtained in the previous problems. Modify the MATLAB script you can generate from`cameraCalibrator`

so you can nicely publish the results. - Use either calibration toolkit with the images from 21:27 and compare the results to the previous problems.
- Extract the top row of corner points from the calibration results each for severai images (21:27) (either toolkit).
Find the angle θ for each of the lines minimizing the perpendicular distance to the lines.
Transform the points to the (
*u*,*v*) coordinate system for each line and plot*v*vs.*u*. If you see a quadratic deviation, fit a quadratic polynomial to the transformed points - Generate a photo montage showing various views of the cube from the last assignment. Include several views showing the effect of perspective projection with the camera angle varying from large (maybe 60-degrees to small 10-degrees).
- Read chapter 2 from
Peter Corke, Use the*Robotics, vision and control: fundamental algorithms in MATLAB*,

Springer, c2011. ISBN 978-3-642-20143-1 [UD library electronic resource]`rvctools`

from the previous assignment.Download the MATLAB chapter 2 code. Please create a MATLAB script, that generates a nicely formatted version of this code, including explanations from the textbook as necessary to understand the theory behind the code.

Maintained by John Loomis,
last updated *7 February 2018 *