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added dedicated <modname>_init.cpp files with initModule_<modname>() functions and all the relevant structures; made BackgroundSubtractorMOG/MOG2 derivatives from Algorithm; cleaned up MOG2 implementation and made it multi-threaded.

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This commit is contained in:
Vadim Pisarevsky
2012-04-20 15:32:54 +00:00
parent 3d108958e7
commit 5b6b30ba0e
19 changed files with 1042 additions and 1199 deletions
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29
modules/video/src/bgfg_gaussmix.cpp
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@@ -134,17 +134,19 @@ template<typename VT> struct MixData
};
static void process8uC1( BackgroundSubtractorMOG& obj, const Mat& image, Mat& fgmask, double learningRate )
static void process8uC1( const Mat& image, Mat& fgmask, double learningRate,
Mat& bgmodel, int nmixtures, double backgroundRatio,
double varThreshold, double noiseSigma )
{
int x, y, k, k1, rows = image.rows, cols = image.cols;
float alpha = (float)learningRate, T = (float)obj.backgroundRatio, vT = (float)obj.varThreshold;
int K = obj.nmixtures;
MixData<float>* mptr = (MixData<float>*)obj.bgmodel.data;
float alpha = (float)learningRate, T = (float)backgroundRatio, vT = (float)varThreshold;
int K = nmixtures;
MixData<float>* mptr = (MixData<float>*)bgmodel.data;
const float w0 = (float)defaultInitialWeight;
const float sk0 = (float)(w0/(defaultNoiseSigma*2));
const float var0 = (float)(defaultNoiseSigma*defaultNoiseSigma*4);
const float minVar = (float)(obj.noiseSigma*obj.noiseSigma);
const float minVar = (float)(noiseSigma*noiseSigma);
for( y = 0; y < rows; y++ )
{
@@ -259,17 +261,20 @@ static void process8uC1( BackgroundSubtractorMOG& obj, const Mat& image, Mat& fg
}
}
static void process8uC3( BackgroundSubtractorMOG& obj, const Mat& image, Mat& fgmask, double learningRate )
static void process8uC3( const Mat& image, Mat& fgmask, double learningRate,
Mat& bgmodel, int nmixtures, double backgroundRatio,
double varThreshold, double noiseSigma )
{
int x, y, k, k1, rows = image.rows, cols = image.cols;
float alpha = (float)learningRate, T = (float)obj.backgroundRatio, vT = (float)obj.varThreshold;
int K = obj.nmixtures;
float alpha = (float)learningRate, T = (float)backgroundRatio, vT = (float)varThreshold;
int K = nmixtures;
const float w0 = (float)defaultInitialWeight;
const float sk0 = (float)(w0/(defaultNoiseSigma*2*sqrt(3.)));
const float var0 = (float)(defaultNoiseSigma*defaultNoiseSigma*4);
const float minVar = (float)(obj.noiseSigma*obj.noiseSigma);
MixData<Vec3f>* mptr = (MixData<Vec3f>*)obj.bgmodel.data;
const float minVar = (float)(noiseSigma*noiseSigma);
MixData<Vec3f>* mptr = (MixData<Vec3f>*)bgmodel.data;
for( y = 0; y < rows; y++ )
{
@@ -403,9 +408,9 @@ void BackgroundSubtractorMOG::operator()(InputArray _image, OutputArray _fgmask,
CV_Assert(learningRate >= 0);
if( image.type() == CV_8UC1 )
process8uC1( *this, image, fgmask, learningRate );
process8uC1( image, fgmask, learningRate, bgmodel, nmixtures, backgroundRatio, varThreshold, noiseSigma );
else if( image.type() == CV_8UC3 )
process8uC3( *this, image, fgmask, learningRate );
process8uC3( image, fgmask, learningRate, bgmodel, nmixtures, backgroundRatio, varThreshold, noiseSigma );
else
CV_Error( CV_StsUnsupportedFormat, "Only 1- and 3-channel 8-bit images are supported in BackgroundSubtractorMOG" );
}