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WeightedMovingVarianceBGS.cpp
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WeightedMovingVarianceBGS.cpp
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/*
This file is part of BGSLibrary.
BGSLibrary is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
BGSLibrary is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with BGSLibrary. If not, see <http://www.gnu.org/licenses/>.
*/
#include "WeightedMovingVarianceBGS.h"
WeightedMovingVarianceBGS::WeightedMovingVarianceBGS() : firstTime(true), enableWeight(true),
enableThreshold(true), threshold(15), showOutput(false)
{
//std::cout << "WeightedMovingVarianceBGS()" << std::endl;
}
WeightedMovingVarianceBGS::~WeightedMovingVarianceBGS()
{
std::cout << "~WeightedMovingVarianceBGS()" << std::endl;
}
void WeightedMovingVarianceBGS::process(const cv::Mat &img_input, cv::Mat &img_output, cv::Mat &img_bgmodel)
{
if(img_input.empty())
return;
loadConfig();
if(firstTime)
saveConfig();
if(img_input_prev_1.empty())
{
img_input.copyTo(img_input_prev_1);
return;
}
if(img_input_prev_2.empty())
{
img_input_prev_1.copyTo(img_input_prev_2);
img_input.copyTo(img_input_prev_1);
return;
}
cv::Mat img_input_f(img_input.size(), CV_32F);
img_input.convertTo(img_input_f, CV_32F, 1./255.);
cv::Mat img_input_prev_1_f(img_input.size(), CV_32F);
img_input_prev_1.convertTo(img_input_prev_1_f, CV_32F, 1./255.);
cv::Mat img_input_prev_2_f(img_input.size(), CV_32F);
img_input_prev_2.convertTo(img_input_prev_2_f, CV_32F, 1./255.);
cv::Mat img_foreground;
// Weighted mean
cv::Mat img_mean_f(img_input.size(), CV_32F);
//CV_32F is float - the pixel can have any value between 0-1.0, this is useful for some sets of calculations on data
if(enableWeight)
img_mean_f = ((img_input_f * 0.5) + (img_input_prev_1_f * 0.3) + (img_input_prev_2_f * 0.2));
else
img_mean_f = ((img_input_f * 0.3) + (img_input_prev_1_f * 0.3) + (img_input_prev_2_f * 0.3));
// Weighted variance
cv::Mat img_1_f(img_input.size(), CV_32F);
cv::Mat img_2_f(img_input.size(), CV_32F);
cv::Mat img_3_f(img_input.size(), CV_32F);
cv::Mat img_4_f(img_input.size(), CV_32F);
if(enableWeight)
{
img_1_f = computeWeightedVariance(img_input_f, img_mean_f, 0.5);
img_2_f = computeWeightedVariance(img_input_prev_1_f, img_mean_f, 0.3);
img_3_f = computeWeightedVariance(img_input_prev_2_f, img_mean_f, 0.2);
img_4_f = (img_1_f + img_2_f + img_3_f);
}
else
{
img_1_f = computeWeightedVariance(img_input_f, img_mean_f, 0.3);
img_2_f = computeWeightedVariance(img_input_prev_1_f, img_mean_f, 0.3);
img_3_f = computeWeightedVariance(img_input_prev_2_f, img_mean_f, 0.3);
img_4_f = (img_1_f + img_2_f + img_3_f);
}
// Standard deviation
cv::Mat img_sqrt_f(img_input.size(), CV_32F);
cv::sqrt(img_4_f, img_sqrt_f);
cv::Mat img_sqrt(img_input.size(), CV_8U);
double minVal, maxVal;
minVal = 0.; maxVal = 1.;
img_sqrt_f.convertTo(img_sqrt, CV_8U, 255.0/(maxVal - minVal), -minVal);
img_sqrt.copyTo(img_foreground);
if(img_foreground.channels() == 3)
cv::cvtColor(img_foreground, img_foreground, CV_BGR2GRAY);
if(enableThreshold)
cv::threshold(img_foreground, img_foreground, threshold, 255, cv::THRESH_BINARY);
//if(showOutput)
//cv::imshow("W Moving Variance", img_foreground);
img_foreground.copyTo(img_output);
img_input_prev_1.copyTo(img_input_prev_2);
img_input.copyTo(img_input_prev_1);
firstTime = false;
}
//unused
cv::Mat WeightedMovingVarianceBGS::computeWeightedMean(const std::vector<cv::Mat> &v_img_input_f, const std::vector<double> weights)
{
cv::Mat img;
return img;
}
cv::Mat WeightedMovingVarianceBGS::computeWeightedVariance(const cv::Mat &img_input_f, const cv::Mat &img_mean_f, const double weight)
{
//ERROR in return (weight * ((cv::abs(img_input_f - img_mean_f))^2.));
cv::Mat img_f_absdiff(img_input_f.size(), CV_32F);
cv::absdiff(img_input_f, img_mean_f, img_f_absdiff);
cv::Mat img_f_pow(img_input_f.size(), CV_32F);
cv::pow(img_f_absdiff, 2.0, img_f_pow);
cv::Mat img_f = weight * img_f_pow;
return img_f;
}
void WeightedMovingVarianceBGS::saveConfig()
{
string xmlDirectory = QCoreApplication::applicationDirPath().toStdString() + "//WeightedMovingVarianceBGS.xml";
const char *xmlDirect = xmlDirectory.c_str();
CvFileStorage* fs = cvOpenFileStorage(xmlDirect, 0, CV_STORAGE_WRITE);
cvWriteInt(fs, "enableWeight", enableWeight);
cvWriteInt(fs, "enableThreshold", enableThreshold);
cvWriteInt(fs, "threshold", threshold);
cvWriteInt(fs, "showOutput", showOutput);
cvReleaseFileStorage(&fs);
}
void WeightedMovingVarianceBGS::loadConfig()
{
string xmlDirectory = QCoreApplication::applicationDirPath().toStdString() + "//WeightedMovingVarianceBGS.xml";
const char *xmlDirect = xmlDirectory.c_str();
CvFileStorage* fs = cvOpenFileStorage(xmlDirect, 0, CV_STORAGE_READ);
enableWeight = cvReadIntByName(fs, 0, "enableWeight", true);
enableThreshold = cvReadIntByName(fs, 0, "enableThreshold", true);
threshold = cvReadIntByName(fs, 0, "threshold", 15);
showOutput = cvReadIntByName(fs, 0, "showOutput", true);
cvReleaseFileStorage(&fs);
}