In this project, the goal was to understand and implement image warping and mosaicing using concepts like homographies.
I decided to shoot photos of the Haas School of Business here at Berkeley with the goal of creating a panorama of the campus.
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Then, I wrote a function to generate the homography between two images and their corresponding points. For this project, I chose ten points in each of the images to use for the homography calculation. To compute the homography, I used least squares, calculating Ah = b, where A is a n x 8 matrix, h is a 8 x 1 matrix of parameters we wish to solve for, and finally b is an nx1 matrix of points, with the x coordinates stacked on top of the y coordinates.
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Attempted to stitch and warp the images using inverse warp.
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The coolest thing I learned in this project is image rectification. It was really cool to create "better looking" images and really understand the mechanism of inverse warping and interpolation.