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#set page(width: 16cm, margin: 0.5em, height: auto)
#let definition(content) = box(fill: luma(92%), width: 100%, inset: 0.5em, stroke: black)[#content]
#let pr = $nu$
#let time = $t$
== Resampling
#let inv = $v$
*Algorithm* : Upsampling\
*Input* : ${inv[k] = (x[k],y[k],t[k]), 0 <= k <= n}$ and a target rate `sampling_min_output_rate`\, Interpolate time and
position between each $k$ by linearly adding interpolated values\
This is done by adding linearly interpolated values so that the output stream is
$
{
inv[0], underbrace(u_0[1]\, dots\, u_0[n_0-1], "interpolated"), inv[
1
], underbrace(u_1[1]\, dots\, u_1[n_1 - 1 ], "interpolated"),inv[2], dots
}
$
Each $n_i$ is the minimum integer such that
$
& (t[i]-t[i-1]) / n_i < Delta_"target"\
<=> & n_i = ceil((t[i+1]-t[i])/Delta_"target")
$
and the linear interpolation means
$
u_j [k] = (1 - k / n_j) inv[j] + k / n_i inv[j+1]
$\
*Output* : ${(x'[k'],y'[k'],t'[k']), 0 <= k; <= n'}$ the upsampled position and times. This verifies $
forall k', t'[k'] - t'[k'-1] < Delta_"target" = 1/#text[`sampling_min_output_rate`]
$\
*Remark* : As this is a streaming algorithm, we only calculate this interpolation with respect to the latest stroke
position.
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