## 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.