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/**
* Double-exponential smoothing based on Wright's modification of Holt's method
* for irregular data.
*
* Copyright 2014 Martin Tschirsich
* Released under the MIT license
*
* @param {Array} alphas Exponential smoothing factors
* @param {Array} initialValues Initial values before smoothing
* @param {Number} lookAhead Additionally added linear trend, between 0 - 1
*/
var Smoother = function(alphas, detection, lookAhead) {
"use strict";
var initialValues = [detection.x, detection.y, detection.width, detection.height];
var lastUpdate = +new Date(),
initialAlphas = alphas.slice(0),
alphas = alphas.slice(0),
a = initialValues.slice(0),
b = initialValues.slice(0),
numValues = initialValues.length,
lookAhead = (typeof lookAhead !== 'undefined') ? lookAhead : 1.0;
this.smooth = function(detection) {
var smoothedValues = [];
// time in seconds since last update:
var time = new Date() - lastUpdate;
lastUpdate += time;
time /= 1000;
var smoothedDetection = detection;
var values = [detection.x, detection.y, detection.width, detection.height];
// update:
for (var i = 0; i < numValues; ++i) {
// Wright's modification of Holt's method for irregular data:
alphas[i] = alphas[i] / (alphas[i] + Math.pow(1 - initialAlphas[i], time));
var oldA = a[i];
a[i] = alphas[i] * values[i] + (1 - alphas[i]) * (a[i] + b[i] * time);
b[i] = alphas[i] * (a[i] - oldA) / time + (1 - alphas[i]) * b[i];
smoothedValues[i] = a[i] + time * lookAhead * b[i];
// Alternative approach:
//a[i] = alphas[i] * values[i] + (1 - alphas[i]) * a[i];
//b[i] = alphas[i] * a[i] + (1 - alphas[i]) * b[i];
//smoothedValues[i] = 2*a[i] - 1*b[i];*/
}
smoothedDetection.x = smoothedValues[0];
smoothedDetection.y = smoothedValues[1];
smoothedDetection.width = smoothedValues[2] > 0 ? smoothedValues[2] : 0;
smoothedDetection.height = smoothedValues[3] > 0 ? smoothedValues[3] : 0;
if(smoothedDetection.width < 0 || smoothedDetection.height < 0)
console.log("dddd");
return smoothedDetection;
};
}