IMAGE WARPING and MOSAICING (Part A), Anusha Syed

Recovering Homographies

In order to compute the projective transform between two images, we need to recover the homography matrix, which consists of 8 unknowns. We are able to do this by finding at least 4 correspondence points between two images. We then solve the following equation using least squares to recover the 8 unknowns to construct the homography matrix:

Rectifying Images

In order to illustrate that we have properly constructed the homography, I warped a couple images with planar objects, below are the result:

I used the four corners of the notebook as my correspondence points

I used the four corners of the picture of Mac Dre as my correspondence points

Mosaicing

Haas

Pictures and mosaic-ed result:

Finished Boba and library table

Pictures and mosaic-ed result:

My friend's house

Pictures and mosaic-ed result:

This result was not the best, I think this was because I picked a poor set of correspondence points and the dimensions of the image were larger. This was most likely the problem because much of my stitching code was based on the dimensions of the image being a certain size.