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modified BackgroundSubtractorMOG2::getBackgroundImage so that it can now work with gray-level images.

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This commit is contained in:
Firat Kalaycilar 2014-03-21 09:44:11 +02:00
parent 034ef02409
commit c9f51d5eed
1 changed files with 24 additions and 29 deletions
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53
modules/video/src/bgfg_gaussmix2.cpp
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@ -577,54 +577,49 @@ void BackgroundSubtractorMOG2::operator()(InputArray _image, OutputArray _fgmask
void BackgroundSubtractorMOG2::getBackgroundImage(OutputArray backgroundImage) const
{
int nchannels = CV_MAT_CN(frameType);
CV_Assert( nchannels == 3 );
Mat meanBackground(frameSize, CV_8UC3, Scalar::all(0));
CV_Assert(nchannels == 1 || nchannels == 3);
Mat meanBackground(frameSize, CV_MAKETYPE(CV_8U, nchannels), Scalar::all(0));
int firstGaussianIdx = 0;
const GMM* gmm = (GMM*)bgmodel.data;
const Vec3f* mean = reinterpret_cast<const Vec3f*>(gmm + frameSize.width*frameSize.height*nmixtures);
const float* mean = reinterpret_cast<const float*>(gmm + frameSize.width*frameSize.height*nmixtures);
for(int row=0; row<meanBackground.rows; row++)
{
for(int col=0; col<meanBackground.cols; col++)
{
int nmodes = bgmodelUsedModes.at<uchar>(row, col);
Vec3f meanVal;
std::vector<float> meanVal(nchannels, 0.f);
float totalWeight = 0.f;
for(int gaussianIdx = firstGaussianIdx; gaussianIdx < firstGaussianIdx + nmodes; gaussianIdx++)
{
GMM gaussian = gmm[gaussianIdx];
meanVal += gaussian.weight * mean[gaussianIdx];
size_t meanPosition = gaussianIdx*nchannels;
for(int chn = 0; chn < nchannels; chn++)
{
meanVal[chn] += gaussian.weight * mean[meanPosition + chn];
}
totalWeight += gaussian.weight;
if(totalWeight > backgroundRatio)
break;
}
meanVal *= (1.f / totalWeight);
meanBackground.at<Vec3b>(row, col) = Vec3b(meanVal);
float invWeight = 1.f/totalWeight;
for(int chn = 0; chn < nchannels; chn++)
{
meanVal[chn] *= invWeight;
}
switch(nchannels)
{
case 1:
meanBackground.at<uchar>(row, col) = (uchar)meanVal[0];
break;
case 3:
meanBackground.at<Vec3b>(row, col) = Vec3b(*reinterpret_cast<Vec3f*>(&meanVal[0]));
break;
}
firstGaussianIdx += nmixtures;
}
}
switch(CV_MAT_CN(frameType))
{
case 1:
{
vector<Mat> channels;
split(meanBackground, channels);
channels[0].copyTo(backgroundImage);
break;
}
case 3:
{
meanBackground.copyTo(backgroundImage);
break;
}
default:
CV_Error(CV_StsUnsupportedFormat, "");
}
meanBackground.copyTo(backgroundImage);
}
}