Submit HTML documentation and MATLAB code on Isidore. See stereo3 for some general hints.

- Use an image set (two images) of your product. Use
`cpselect`

to choose matching points from each image. Use`estimateFundamentalMatrix`

to calculate the Fundamental matrix and verify that img2*F*img1' = 0 for matching image points. Calculate the Essential matrix from the fundamental matrix, using your intrinsic matrix from an earlier calibration. - Use the same image set. Find the extrinsics (
**R**and**T**) using the checkerboard corners. Use the extrinsics to find the Essential matrix. Verify that x2*E*x1' = 0 for matching normalized camera points. Then calculate the Fundamental matrix from the Essential matrix. Compare to the fundamental matrix calculated in the previous problem. - Use the extrinsics obtained in the previous problem to project matching points back to world coordinates. Compare the results to known dimensions of your product.
- Use the same image set and fundamental matrices deterined earlier. Select a feature in
image 1 and its corresponding image point (img1) to determine the epipolar line in image 2. Draw the
line on image 2 and verify that it passes through (or very close to) the matching point in image 2.
Draw two such epipolar lines and calculate their intersection. Show that this point (epipole) can be
obtained from
`null(F)`

. - Use the extrinsics for your stereo images, reproduce camera views of the checkerboard and compare to the original images.
- Experiment with feature detection methods, using your stereo images. Try all of the methods defined in the Computer Vision toolbox, and compare the results.

Maintained by John Loomis,
last updated *18 April 2016 *