He based this on the homophony and homography of the first singular, and 'homophony' of the 2nd singular pronoun. ❋ Unknown (2007)
What you write is as important as the way you read it which increases the risk of execution for scribes who are not careful enough about homophony, homography, and literary connotations ; one emperor's tendency to paranoïa critique is often deadly. ❋ Unknown (2004)
Step 4: Project and blend the second image using the homography ❋ César De Souza (2010)
Step 3: Create the homography matrix using a robust estimator ❋ César De Souza (2010)
After our homography matrix has been computed, all that is left for us is to blend the two images together. ❋ César De Souza (2010)
RansacHomographyEstimator class for estimating homography matrices using RANSAC. ❋ César De Souza (2010)
RANSAC object with the parameters for fitting an homography matrix. ❋ César De Souza (2010)
By estimating the correct values for the homography matrix, we could obtain a transformation like the following: ❋ César De Souza (2010)
In more formal terms, a homography is an invertible transformation from the real projective plane to the projective plane that maps straight lines to straight lines. ❋ César De Souza (2010)
For the problem of homography estimation, RANSAC works by trying to fit several models using some of the points pairs and then checking if the models were able to relate most of the points. ❋ César De Souza (2010)
What we are looking for is some kind of image transformation which can be used to project one of the two images on top of the other while matching most of the correlated feature points - we need an homography matrix matching the two images. ❋ César De Souza (2010)
The best model, i.e. the homography which produces the highest number of correct matches, is then chosen as the answer for the problem. ❋ César De Souza (2010)
Now that we have defined what an homography is and what it is useful for, we can begin to discuss how we can create this homography matrix from our set of correlated points. ❋ César De Souza (2010)
Blend blend = new Blend (homography, img1); pictureBox. ❋ César De Souza (2010)
Remember we will need to perform four steps: Interest point detection, Correlation matching, Robust homography estimation and Gradient blending. ❋ César De Souza (2010)
Alignment: Notification of disabled homography due to too few points ❋ Unknown (2009)
Alignment: New homography based method, in addition to the unconstraint one ❋ Unknown (2009)
If you want some fancy words for how puns can be created, consider homophony, homography, homonomy, or polysemy. ❋ Unknown (2009)
How about trying a similar exercise with homography? ❋ Unknown (1986)
