In this project we took pictures of the same scene from multiple angles and recovered a transformation between the two views so that we could stitch the images together into a single mosaic. This was done by identifying corresponding points between the two images and recovering a homography that transformed points in one coordinate frame to the other. Please see the code for this project for an example of how this homography was calculated.
For the first part of the project we "rectified" single images by identifying areas of the picture that we knew were rectangular in real life but did not appear to be so in the picture because of the perspective. We then warped these pictures into a coordinate frame where the object did appear rectangular, thus "rectifying" it to a rectangular frame. Two examples of this - a window and a poster - are included below
the rectified version, with the window now rectangular:
the rectified version, with the poster now rectangular:
For the next part we stitched together multiple images taken at different angles into a single coherent image. This was challenging because modern cameras automatically change the focus and exposure according to the environmental condiditons so it was difficult to get two images in which the lighting and other conditions matched up well. We partially ameliorated this issue by performing a blending of the images so that the seam between them did not appear as prominent but it did not always work correctly. Included below are the source images and resulting blended mosaics for three examples, showing that blending does not always work correctly.