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Consider frame i captured at time t.
This means that we need to store every frame, because the frame i + 1 requires frame i-2 as a reference.
The data (frame i) structure of the proposed system is shown in Figure 1a.
This latter aims to find for each feature point (called also interest point), detected on the video frame (i), a corresponding feature point, detected on the video frame (i+1).
As manifested from observers, the abrupt changes of negative parallax in a positive/negative parallax environment provoke a high visual discomfort in the observer's eye: Discomfort ≡ Average P < 0 frame i − Average P < 0 frame i + n > 10%% (3).
Towards this aim, we relate the visual quality u i of the i th frame to the root mean square value (RMSV) σ i of the innovation process between frame i and frame i−1.
When aligning frame i with frame i + 1, we carry as much color information as possible from the previous alignment of frame i - 1 with frame i.
This ensures that cells entering the scene in frame i can be identified in frame i (rather than frame i + 1).
The second stage then performs the linking of consecutive frames by assigning the cells identified in frame i to the cells identified in frame i + 1.
In order to trace one cell, we match a set of segments in frame i onto another set of segments in frame i + 1.
In the second stage – the so-called linking stage – our newly developed topological alignment links segments between each frame i and the next frame i + 1.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com