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Input images for evaluation of plane position estimation.
Figure 7 Input images for evaluation of plane position estimation.
At first, two consecutive frames are used as input images for the proposed system.
There are 33 frames used as the input images for SfM methods (one fifteenth of 486 frames).
Surrounding red boxes indicate that these distances are included in a set of input images for light field estimation.
Each variable pattern of light source positions (a) - (e) corresponds to variational position of virtual light sources in Fig. 12. Surrounding red boxes indicate that these distances are included in a set of input images for light field estimation.
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This output is finally denormalized to the same range as the input image for illustration purposes.
It is worth noting here that we consider the original (unwatermarked) version of an image as the input image for the watermarking functions.
This operator scans the input image for a circle having a maximum gradient change along a circular arc of radius and center coordinates.
Many operations may be necessary to prepare a raw input image for recognition, such as the selection of an interesting area, the elimination of nonmusical elements, image binarization, and the correction of image rotation.
In other words, we only need to compute the comparative relation of the input image for k times, where k can be a small number and much less than N. Therefore, the computational cost of our approach is reasonable.
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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