/* Copyright (c) 2014 Donovan Baarda * * 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 #include #include #include "opentrack/plugin-api.hpp" #include #include // 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. auto dt = timer.restart() / 1000.0f; // 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(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)