Description
1 Part A
[3.5 points] Take a A4 paper which is 210×297(unit: millimeter). Attach the
paper on a door. Take a picture of the door such that all four corners of the door
are visible on the photo. Take this picture in an oblique view, ie, the door is not
a perfect rectangle but rather a quadrilateral in the photo. Using homography
theory, estimate the width and height of the door from the picture. Show your
derivation, captured image and final result.
2 Part B
[5.5 points] Take 3 images of yourself holding a hardcover book (which we call
them im1.jpg, im2.jpg,im3.jpg). If you use a mirror, remember to flip the images
horizontally. Try to make one of the images easy (little out of plane rotation;
but do include in-plane rotations); one of the images somewhat more difficult
(e.g. a bit further away from the camera and also include 30-40 degrees out
of plane rotation; change the lighting a bit); and one of the images difficult
(further away, or 40-60 degrees out of plan rotation, or drastically change the
lighting). Also, find a picture of the book cover on Amazon or another website
(which we call it bookCover.jpg). Finally, download a cover of another book from
Amazon or another website (which we call it anotherBookCover.jpg). Reduce the
image sizes so none is larger than 640×480 and save them in a compressed (jpg)
format so your assignment file is not too large (MarkUs does not allow very large
submissions).
(a) [1 points] use SIFT (or any other descriptor you like, e.g. SURF) to
find point matches between each image (im1, im2, im3) and the book cover
(bookCover). Visualize the matches between bookCover and each of the 3 images
in a manner similar to slide #10 on lecture8-B. You can use any implementation
of SIFT (or SURF or …) in Python (OpenCV) or Matlab.
(b) [1 point] visually estimate the percentage of outliers in each case and compute the number of RANSAC iterations to recover the an affine transformation
between bookCover and each of the images with a ¿=99% chance Similarly, estimate the number of iterations required to recover the projective transformation
(homography).
2 A3
(c) [1 point] using RANSAC (any open source implementation, or your own),
find the affine transformation between bookCover and im1, im2, and im3. Use
this transformation to paste bookCover onto each of the images. Explain when
the method is successful and when it might fail.
(d) [1.5 point] use a homography (protective transformation) to do the same.
Explain when the method is successful and when it might fail. Compare and
discuss the differences.
(e) [1 point] use a homography to map the cover of the second book (another
BookCover) onto each image. Discuss your results.
3 Part C
[3 point] Using your phone or any camera you have(select a specific resolution),
estimate the internal parameter matrix K for your camera. Show your plan,
formula derivation, captured picture and result. To be simple, assume there is
no distortion and focal length is the same for both x axis and y axis. If you use
libraries, you can get at most 1.5 points.
4 Part D
[Extra credit: 3 points] Use all provided landscape images to create the panorama. Read about Poisson blending (http://eric-yuan.me/poisson-blending/) and
use it to make your panorama look better.
