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/* Copyright (c) 2014 Donovan Baarda <abo@minkirri.apana.org.au>
*
* Permission to use, copy, modify, and/or distribute this software for any
* purpose with or without fee is hereby granted, provided that the above
* copyright notice and this permission notice appear in all copies.
*/
#include "ftnoir_filter_ewma2.h"
#include <cmath>
#include <QDebug>
#include <QWidget>
#include "opentrack/plugin-api.hpp"
#include <algorithm>
#include <QMutexLocker>
// Exponentially Weighted Moving Average (EWMA) Filter with dynamic smoothing.
//
// This filter tries to adjust the amount of filtering to minimize lag when
// moving, and minimize noise when still. It uses the delta filtered over the
// last 1/60sec (16ms) compared to the delta's average noise variance over
// the last 60sec to try and detect movement vs noise. As the delta increases
// from 0 to 3 stdevs of the noise, the filtering scales down from maxSmooth
// to minSmooth at a rate controlled by the powCurve setting.
FTNoIR_Filter::FTNoIR_Filter()
{
reset();
}
void FTNoIR_Filter::receiveSettings()
{
s.b->reload();
}
void FTNoIR_Filter::reset()
{
timer.invalidate();
}
void FTNoIR_Filter::filter(const double *input, double *output)
{
// Start the timer and initialise filter state if it's not running.
if (!timer.isValid()) {
timer.start();
for (int i=0;i<6;i++) {
last_output[i] = input[i];
last_delta[i] = 0.0;
last_noise[i] = 0.0;
}
}
// Get the time in seconds since last run and restart the timer.
const double dt = timer.restart() / 1000.;
// Calculate delta_alpha and noise_alpha from dt.
double delta_alpha = dt/(dt + delta_RC);
double noise_alpha = dt/(dt + noise_RC);
// Calculate the new camera position.
for (int i=0;i<6;i++) {
// Calculate the current and smoothed delta.
double delta = input[i] - last_output[i];
last_delta[i] = delta_alpha*delta + (1.0-delta_alpha)*last_delta[i];
// Calculate the current and smoothed noise variance.
double noise = last_delta[i]*last_delta[i];
last_noise[i] = noise_alpha*noise + (1.0-noise_alpha)*last_noise[i];
// Normalise the noise between 0->1 for 0->9 variances (0->3 stddevs).
double norm_noise = std::min<double>(noise/(9.0*last_noise[i]), 1.0);
if (std::isnan(norm_noise))
norm_noise = 0;
// Calculate the smoothing 0.0->1.0 from the normalized noise.
// TODO(abo): change kSmoothingScaleCurve to a float where 1.0 is sqrt(norm_noise).
double smoothing = 1.0 - pow(norm_noise, s.kSmoothingScaleCurve/20.0);
// Currently min/max smoothing are ints 0->100. We want 0.0->3.0 seconds.
// TODO(abo): Change kMinSmoothing, kMaxSmoothing to floats 0.0->3.0 seconds RC.
double RC = 3.0*(s.kMinSmoothing + smoothing*(s.kMaxSmoothing - s.kMinSmoothing))/100.0;
// Calculate the dynamic alpha.
double alpha = dt/(dt + RC);
// Calculate the new output position.
output[i] = last_output[i] = alpha*input[i] + (1.0-alpha)*last_output[i];
}
}
OPENTRACK_DECLARE_FILTER(FTNoIR_Filter, FilterControls, FTNoIR_FilterDll)
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