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added updateBackgroundModel parameter and release method

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This commit is contained in:
Vladislav Vinogradov
2012-08-09 14:37:08 +04:00
parent 55f8310cac
commit bfd9e6102a
3 changed files with 44 additions and 17 deletions
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46
modules/video/src/bgfg_gmg.cpp
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@@ -60,6 +60,7 @@ cv::BackgroundSubtractorGMG::BackgroundSubtractorGMG()
backgroundPrior = 0.8;
decisionThreshold = 0.8;
smoothingRadius = 7;
updateBackgroundModel = true;
}
cv::BackgroundSubtractorGMG::~BackgroundSubtractorGMG()
@@ -199,11 +200,11 @@ namespace
public:
GMG_LoopBody(const cv::Mat& frame, const cv::Mat& fgmask, const cv::Mat_<int>& nfeatures, const cv::Mat_<int>& colors, const cv::Mat_<float>& weights,
int maxFeatures, double learningRate, int numInitializationFrames, int quantizationLevels, double backgroundPrior, double decisionThreshold,
double maxVal, double minVal, int frameNum) :
double maxVal, double minVal, int frameNum, bool updateBackgroundModel) :
frame_(frame), fgmask_(fgmask), nfeatures_(nfeatures), colors_(colors), weights_(weights),
maxFeatures_(maxFeatures), learningRate_(learningRate), numInitializationFrames_(numInitializationFrames),
quantizationLevels_(quantizationLevels), backgroundPrior_(backgroundPrior), decisionThreshold_(decisionThreshold),
maxVal_(maxVal), minVal_(minVal), frameNum_(frameNum)
maxVal_(maxVal), minVal_(minVal), frameNum_(frameNum), updateBackgroundModel_(updateBackgroundModel)
{
}
@@ -224,6 +225,7 @@ namespace
int quantizationLevels_;
double backgroundPrior_;
double decisionThreshold_;
bool updateBackgroundModel_;
double maxVal_;
double minVal_;
@@ -275,18 +277,21 @@ namespace
// update histogram.
for (int i = 0; i < nfeatures; ++i)
weights[i] *= 1.0f - learningRate_;
bool inserted = insertFeature(newFeatureColor, learningRate_, colors, weights, nfeatures, maxFeatures_);
if (inserted)
if (updateBackgroundModel_)
{
normalizeHistogram(weights, nfeatures);
nfeatures_row[x] = nfeatures;
for (int i = 0; i < nfeatures; ++i)
weights[i] *= 1.0f - learningRate_;
bool inserted = insertFeature(newFeatureColor, learningRate_, colors, weights, nfeatures, maxFeatures_);
if (inserted)
{
normalizeHistogram(weights, nfeatures);
nfeatures_row[x] = nfeatures;
}
}
}
else
else if (updateBackgroundModel_)
{
// training-mode update
@@ -323,12 +328,25 @@ void cv::BackgroundSubtractorGMG::operator ()(InputArray _frame, OutputArray _fg
GMG_LoopBody body(frame, fgmask, nfeatures_, colors_, weights_,
maxFeatures, learningRate, numInitializationFrames, quantizationLevels, backgroundPrior, decisionThreshold,
maxVal_, minVal_, frameNum_);
maxVal_, minVal_, frameNum_, updateBackgroundModel);
cv::parallel_for_(cv::Range(0, frame.rows), body);
cv::medianBlur(fgmask, buf_, smoothingRadius);
cv::swap(fgmask, buf_);
if (smoothingRadius > 0)
{
cv::medianBlur(fgmask, buf_, smoothingRadius);
cv::swap(fgmask, buf_);
}
// keep track of how many frames we have processed
++frameNum_;
}
void cv::BackgroundSubtractorGMG::release()
{
frameSize_ = cv::Size();
nfeatures_.release();
colors_.release();
weights_.release();
buf_.release();
}

4
modules/video/src/video_init.cpp
View File

@@ -78,7 +78,9 @@ CV_INIT_ALGORITHM(BackgroundSubtractorGMG, "BackgroundSubtractor.GMG",
obj.info()->addParam(obj, "smoothingRadius", obj.smoothingRadius,false,0,0,
"Radius of smoothing kernel to filter noise from FG mask image.");
obj.info()->addParam(obj, "decisionThreshold", obj.decisionThreshold,false,0,0,
"Threshold for FG decision rule. Pixel is FG if posterior probability exceeds threshold."));
"Threshold for FG decision rule. Pixel is FG if posterior probability exceeds threshold.");
obj.info()->addParam(obj, "updateBackgroundModel", obj.updateBackgroundModel,false,0,0,
"Perform background model update."));
bool initModule_video(void)
{