void AdaptiveBackgroundLearning::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_background.empty())
img_input.copyTo(img_background);
cv::Mat img_input_f(img_input.size(), CV_32F);
img_input.convertTo(img_input_f, CV_32F, 1./255.);
cv::Mat img_background_f(img_background.size(), CV_32F);
img_background.convertTo(img_background_f, CV_32F, 1./255.);
cv::Mat img_diff_f(img_input.size(), CV_32F);
cv::absdiff(img_input_f, img_background_f, img_diff_f);
if((limit >= 0 && limit > counter) || limit < 0)
{
img_background_f = alpha*img_input_f + (1-alpha)*img_background_f;
cv::Mat img_new_background(img_input.size(), CV_8U);
img_background_f.convertTo(img_new_background, CV_8U, 255.0/(maxVal - minVal), -minVal);
img_new_background.copyTo(img_background);
counter=0;
}
else counter++;
cv::Mat img_foreground(img_input.size(), CV_8U);
img_diff_f.convertTo(img_foreground, CV_8U, 255.0/(maxVal - minVal), -minVal);
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(showForeground)
cv::imshow("A-Learning FG", img_foreground);
if(showBackground)
cv::imshow("A-Learning BG", img_background);
img_foreground.copyTo(img_output);
img_background.copyTo(img_bgmodel);
firstTime = false;
}
void WeightedMovingMeanBGS::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_background_f(img_input.size(), CV_32F);
if(enableWeight)
img_background_f = ((img_input_f * 0.5) + (img_input_prev_1_f * 0.3) + (img_input_prev_2_f * 0.2));
else
img_background_f = ((img_input_f) + (img_input_prev_1_f) + (img_input_prev_2_f)) / 3.0;
cv::Mat img_background(img_background_f.size(), CV_8U);
double minVal, maxVal;
minVal = 0.; maxVal = 1.;
img_background_f.convertTo(img_background, CV_8U, 255.0/(maxVal - minVal), -minVal);
if(showBackground)
cv::imshow("W Moving Mean BG Model", img_background);
cv::Mat img_foreground;
cv::absdiff(img_input, img_background, 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 Mean FG Mask", img_foreground);
img_foreground.copyTo(img_output);
img_background.copyTo(img_bgmodel);
img_input_prev_1.copyTo(img_input_prev_2);
img_input.copyTo(img_input_prev_1);
firstTime = false;
}
