Computer Vision – Problem Set 3 Sunil Bandla – SB36982

Part 1: 1. UT Tower mosaic

2. Input images

Output mosaic

3. Input

Output mosaic

Part II: 2. Correspondence set with outlier highlighted in red

Homography was computed based on the above set of correspondences. The points in the second image were then transformed to points in the first image to check the accuracy of homography computed and below are the results. The final mosaic was also computed using the same homography.

This time, homography was computed using RANSAC algorithm. Below are the transformed points in the first image and the mosaic.

3. Input images

Rectified output

Input images

Rectified output

Sources:

Hospital corridor -

http://www.finishlinefloors.com/rejuvenate_Floor_Finish.php

Ghost - http://www.takoma.com/kids/2010/11/haunted-house-comes-

alive-on-a.html

Blackboard -

http://www.spalding.org/index.php?tname=professional%20developmen

t&p=SCTinstructions

Mirror - http://www.corbisimages.com/Enlargement/42-23010529.html

Rangoli - http://clintoncolbyvincent.blogspot.com/2011/03/theme-

based-rangoli-designs-for.html