Download the images above.
Download point correspondences between every pair of adjacent images (10 matches each) from the upload system (InputData). The correspondences is stored in a single array (cell matrix in matlab), such that for image pair i-j, the points in the image i are in U[i-1,j-1] (python) or U{i,j} (matlab) and in the image j are in U[j-1,i-1] or U{j,i}.
Find homographies H_ij for every pair of adjacent images by the same method (optimizing 4 over 10) as in HW-05; use your u2h_optim function for each homography.
Draw graph of transfer errors, sorted from lower to higher, of all neighboring pairs into a single image. Use different colour for every image pair, export as 06_errors.pdf.
Compute homographies H_i4 for every i ∈ <1,7> that maps the images above into the reference image 04 (thus H_44 is identity). Also construct inverse homographies H_4i.
Plot the image borders of the images 02 to 06 transformed by appropriate homography to the image plane of the image 04. Export as 06_borders.pdf.
Construct a projective panoramic image from the images 03, 04, and 05, in the image plane of the image 04. Save as 06_panorama.png.
Construct calibration matrix K using the actual image size and the original EXIF. All the images share the same calibration. Store it in 06_data.mat
Establish a transformation between each image plane and the coordinate system of the cylinder.
Plot the image borders of all the images mapped onto the cylinder (06_borders_c.pdf).
Construct a panoramic image from all the images mapped onto the cylinder (06_panorama_c.png).
