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added support of all types to BackgroundSubtractorGMG

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This commit is contained in:
Vladislav Vinogradov 2012-08-13 10:28:42 +04:00
parent 9c75ff43ba
commit 4dbc7600e7
2 changed files with 32 additions and 43 deletions
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2
modules/video/include/opencv2/video/background_segm.hpp
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@ -251,7 +251,7 @@ private:
int frameNum_;
cv::Mat_<int> nfeatures_;
cv::Mat_<int> colors_;
cv::Mat_<uint> colors_;
cv::Mat_<float> weights_;
cv::Mat buf_;

73
modules/video/src/bgfg_gmg.cpp
View File

@ -91,7 +91,7 @@ void cv::BackgroundSubtractorGMG::initialize(cv::Size frameSize, double min, dou
namespace
{
float findFeature(int color, const int* colors, const float* weights, int nfeatures)
float findFeature(uint color, const uint* colors, const float* weights, int nfeatures)
{
for (int i = 0; i < nfeatures; ++i)
{
@ -116,7 +116,7 @@ namespace
}
}
bool insertFeature(int color, float weight, int* colors, float* weights, int& nfeatures, int maxFeatures)
bool insertFeature(uint color, float weight, uint* colors, float* weights, int& nfeatures, int maxFeatures)
{
int idx = -1;
for (int i = 0; i < nfeatures; ++i)
@ -134,7 +134,7 @@ namespace
{
// move feature to beginning of list
::memmove(colors + 1, colors, idx * sizeof(int));
::memmove(colors + 1, colors, idx * sizeof(uint));
::memmove(weights + 1, weights, idx * sizeof(float));
colors[0] = color;
@ -144,7 +144,7 @@ namespace
{
// discard oldest feature
::memmove(colors + 1, colors, (nfeatures - 1) * sizeof(int));
::memmove(colors + 1, colors, (nfeatures - 1) * sizeof(uint));
::memmove(weights + 1, weights, (nfeatures - 1) * sizeof(float));
colors[0] = color;
@ -166,45 +166,31 @@ namespace
namespace
{
template <int cn> struct Quantization_
{
template <typename T>
static inline int apply(T val, double minVal, double maxVal, int quantizationLevels)
{
int res = 0;
res |= static_cast<int>((val[0] - minVal) * quantizationLevels / (maxVal - minVal));
res |= static_cast<int>((val[1] - minVal) * quantizationLevels / (maxVal - minVal)) << 8;
res |= static_cast<int>((val[2] - minVal) * quantizationLevels / (maxVal - minVal)) << 16;
return res;
}
};
template <> struct Quantization_<1>
{
template <typename T>
static inline int apply(T val, double minVal, double maxVal, int quantizationLevels)
{
return static_cast<int>((val - minVal) * quantizationLevels / (maxVal - minVal));
}
};
template <typename T> struct Quantization
{
static int apply(const void* src_, int x, double minVal, double maxVal, int quantizationLevels)
static uint apply(const void* src_, int x, int cn, double minVal, double maxVal, int quantizationLevels)
{
const T* src = static_cast<const T*>(src_);
return Quantization_<cv::DataType<T>::channels>::apply(src[x], minVal, maxVal, quantizationLevels);
src += x * cn;
uint res = 0;
for (int i = 0, shift = 0; i < cn; ++i, ++src, shift += 8)
res |= static_cast<int>((*src - minVal) * quantizationLevels / (maxVal - minVal)) << shift;
return res;
}
};
class GMG_LoopBody : public cv::ParallelLoopBody
{
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,
GMG_LoopBody(const cv::Mat& frame, const cv::Mat& fgmask, const cv::Mat_<int>& nfeatures, const cv::Mat_<uint>& colors, const cv::Mat_<float>& weights,
int maxFeatures, double learningRate, int numInitializationFrames, int quantizationLevels, double backgroundPrior, double decisionThreshold,
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), updateBackgroundModel_(updateBackgroundModel)
maxFeatures_(maxFeatures), learningRate_(learningRate), numInitializationFrames_(numInitializationFrames), quantizationLevels_(quantizationLevels),
backgroundPrior_(backgroundPrior), decisionThreshold_(decisionThreshold), updateBackgroundModel_(updateBackgroundModel),
maxVal_(maxVal), minVal_(minVal), frameNum_(frameNum)
{
}
@ -216,7 +202,7 @@ namespace
mutable cv::Mat_<uchar> fgmask_;
mutable cv::Mat_<int> nfeatures_;
mutable cv::Mat_<int> colors_;
mutable cv::Mat_<uint> colors_;
mutable cv::Mat_<float> weights_;
int maxFeatures_;
@ -234,20 +220,23 @@ namespace
void GMG_LoopBody::operator() (const cv::Range& range) const
{
typedef int (*func_t)(const void* src_, int x, double minVal, double maxVal, int quantizationLevels);
static const func_t funcs[6][4] =
typedef uint (*func_t)(const void* src_, int x, int cn, double minVal, double maxVal, int quantizationLevels);
static const func_t funcs[] =
{
{Quantization<uchar>::apply, 0, Quantization<cv::Vec3b>::apply, Quantization<cv::Vec4b>::apply},
{0,0,0,0},
{Quantization<ushort>::apply, 0, Quantization<cv::Vec3w>::apply, Quantization<cv::Vec4w>::apply},
{0,0,0,0},
{0,0,0,0},
{Quantization<float>::apply, 0, Quantization<cv::Vec3f>::apply, Quantization<cv::Vec4f>::apply},
Quantization<uchar>::apply,
Quantization<schar>::apply,
Quantization<ushort>::apply,
Quantization<short>::apply,
Quantization<int>::apply,
Quantization<float>::apply,
Quantization<double>::apply
};
const func_t func = funcs[frame_.depth()][frame_.channels() - 1];
const func_t func = funcs[frame_.depth()];
CV_Assert(func != 0);
const int cn = frame_.channels();
for (int y = range.start, featureIdx = y * frame_.cols; y < range.end; ++y)
{
const uchar* frame_row = frame_.ptr(y);
@ -257,10 +246,10 @@ namespace
for (int x = 0; x < frame_.cols; ++x, ++featureIdx)
{
int nfeatures = nfeatures_row[x];
int* colors = colors_[featureIdx];
uint* colors = colors_[featureIdx];
float* weights = weights_[featureIdx];
int newFeatureColor = func(frame_row, x, minVal_, maxVal_, quantizationLevels_);
uint newFeatureColor = func(frame_row, x, cn, minVal_, maxVal_, quantizationLevels_);
bool isForeground = false;