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The vehicle position is transferred into the second image.
Using this alignment transformation all keypoints in the first image are transformed into the second image.
We then define the uncertainty ϵ auto as the positive number given by ϵ auto 2 = 1 N − 1 ∑ i = 1 N ϵ auto i 2. This is the same expression used in the definition of the intrinsic uncertainty of the manual registration, except that this time the automatically determined transformation T auto is used to map the manually detected keypoints { x i } from the first image into the second image.
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After we decide H, we can take the point coordinate from the first images into equation and compute the corresponding coordinate in the second image, as shown in Figure 9. Figure 9 Corresponding points in two images.
Chen et al. in [20] first used an affine model to transform the second image into a reference image coordinate, and then they repeated the matching process again on the transformed image.
Formally, we capture this as a partitioning problem: We identify the segmentation of the first image into m segments with an index set P = {1,..., m}, and the segmentation of the second image into n segments with an index set Q = {1,..., n}.
What's the first image that floats into your mind?
"Close your eyes and focus on the first image that pops into your head when I say 'nature'," Dr Larry Weiss tells me over the phone.
Quick! What's the first image that pops into your mind when someone says feminist?
After smoothing, the first image is segmented into different regions by a mean shift algorithm.
Boba can be enjoyed by themselves, but they're also a great addition to just about anything, though the first image that pops into mind is tea.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com