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The proposed formulation incorporates both pixel intensity and texture feature in the optical flow objective function such that the interpolation at the intermediate frame is directly modeled.
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The comparison reveals that the poorly-confined frame has been essentially upgraded to the intermediate frame.
In order to find the intermediate frame I x,n), we need to minimize the energy given by Eq. (6).
All of them assume key frames are intracoded, and the intermediate frames are entirely WZ coded.
WZ (Wyner-Ziv) uses hash codes to decode the intermediate frames.
Population analysis for the intermediate frames was done in a similar fashion.
Here, we make an assumption that the intensity of the pixel at intermediate frame as estimated from both neighboring frame is robust, if the optical flow estimation at that pixel is accurate; otherwise, we fill the missing region using flow direction through inpainting along the flow lines.
For our experiment, we set a correlation value of 0.75 between neighboring frames to decide if the computed intermediate frame is suitable for diagnosis.
Both Cartesian and internal intermediate frames are stored in a very compressed manner - less than 10% of the size of the object per intermediate frame for Cartesian and around 1 to 2% smaller for internal coordinate intermediate frames.
Analyses are also performed for a geometrically similar frame designed with the more restrictive requirements of an intermediate frame for comparison with the poorly-confined and retrofitted frames.
To accomplish a smooth transition between these keyframes, image warping is used to create the appropriate intermediate frames.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com