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refactored FGD algorithm

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This commit is contained in:
Vladislav Vinogradov 2013-05-07 12:04:21 +04:00
parent 697793090d
commit 62edeeed16
8 changed files with 459 additions and 532 deletions
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108
modules/gpubgsegm/include/opencv2/gpubgsegm.hpp
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@ -50,9 +50,6 @@
#include "opencv2/core/gpu.hpp"
#include "opencv2/video/background_segm.hpp"
#include <memory>
#include "opencv2/gpufilters.hpp"
namespace cv { namespace gpu {
////////////////////////////////////////////////////
@ -105,76 +102,51 @@ public:
CV_EXPORTS Ptr<gpu::BackgroundSubtractorGMG>
createBackgroundSubtractorGMG(int initializationFrames = 120, double decisionThreshold = 0.8);
////////////////////////////////////////////////////
// FGD
// Foreground Object Detection from Videos Containing Complex Background.
// Liyuan Li, Weimin Huang, Irene Y.H. Gu, and Qi Tian.
// ACM MM2003 9p
class CV_EXPORTS FGDStatModel
/**
* Foreground Object Detection from Videos Containing Complex Background.
* Liyuan Li, Weimin Huang, Irene Y.H. Gu, and Qi Tian.
* ACM MM2003 9p
*/
class CV_EXPORTS BackgroundSubtractorFGD : public cv::BackgroundSubtractor
{
public:
struct CV_EXPORTS Params
{
int Lc; // Quantized levels per 'color' component. Power of two, typically 32, 64 or 128.
int N1c; // Number of color vectors used to model normal background color variation at a given pixel.
int N2c; // Number of color vectors retained at given pixel. Must be > N1c, typically ~ 5/3 of N1c.
// Used to allow the first N1c vectors to adapt over time to changing background.
int Lcc; // Quantized levels per 'color co-occurrence' component. Power of two, typically 16, 32 or 64.
int N1cc; // Number of color co-occurrence vectors used to model normal background color variation at a given pixel.
int N2cc; // Number of color co-occurrence vectors retained at given pixel. Must be > N1cc, typically ~ 5/3 of N1cc.
// Used to allow the first N1cc vectors to adapt over time to changing background.
bool is_obj_without_holes; // If TRUE we ignore holes within foreground blobs. Defaults to TRUE.
int perform_morphing; // Number of erode-dilate-erode foreground-blob cleanup iterations.
// These erase one-pixel junk blobs and merge almost-touching blobs. Default value is 1.
float alpha1; // How quickly we forget old background pixel values seen. Typically set to 0.1.
float alpha2; // "Controls speed of feature learning". Depends on T. Typical value circa 0.005.
float alpha3; // Alternate to alpha2, used (e.g.) for quicker initial convergence. Typical value 0.1.
float delta; // Affects color and color co-occurrence quantization, typically set to 2.
float T; // A percentage value which determines when new features can be recognized as new background. (Typically 0.9).
float minArea; // Discard foreground blobs whose bounding box is smaller than this threshold.
// default Params
Params();
};
// out_cn - channels count in output result (can be 3 or 4)
// 4-channels require more memory, but a bit faster
explicit FGDStatModel(int out_cn = 3);
explicit FGDStatModel(const cv::gpu::GpuMat& firstFrame, const Params& params = Params(), int out_cn = 3);
~FGDStatModel();
void create(const cv::gpu::GpuMat& firstFrame, const Params& params = Params());
void release();
int update(const cv::gpu::GpuMat& curFrame);
//8UC3 or 8UC4 reference background image
cv::gpu::GpuMat background;
//8UC1 foreground image
cv::gpu::GpuMat foreground;
std::vector< std::vector<cv::Point> > foreground_regions;
private:
FGDStatModel(const FGDStatModel&);
FGDStatModel& operator=(const FGDStatModel&);
class Impl;
std::auto_ptr<Impl> impl_;
virtual void getForegroundRegions(OutputArrayOfArrays foreground_regions) = 0;
};
struct CV_EXPORTS FGDParams
{
int Lc; // Quantized levels per 'color' component. Power of two, typically 32, 64 or 128.
int N1c; // Number of color vectors used to model normal background color variation at a given pixel.
int N2c; // Number of color vectors retained at given pixel. Must be > N1c, typically ~ 5/3 of N1c.
// Used to allow the first N1c vectors to adapt over time to changing background.
int Lcc; // Quantized levels per 'color co-occurrence' component. Power of two, typically 16, 32 or 64.
int N1cc; // Number of color co-occurrence vectors used to model normal background color variation at a given pixel.
int N2cc; // Number of color co-occurrence vectors retained at given pixel. Must be > N1cc, typically ~ 5/3 of N1cc.
// Used to allow the first N1cc vectors to adapt over time to changing background.
bool is_obj_without_holes; // If TRUE we ignore holes within foreground blobs. Defaults to TRUE.
int perform_morphing; // Number of erode-dilate-erode foreground-blob cleanup iterations.
// These erase one-pixel junk blobs and merge almost-touching blobs. Default value is 1.
float alpha1; // How quickly we forget old background pixel values seen. Typically set to 0.1.
float alpha2; // "Controls speed of feature learning". Depends on T. Typical value circa 0.005.
float alpha3; // Alternate to alpha2, used (e.g.) for quicker initial convergence. Typical value 0.1.
float delta; // Affects color and color co-occurrence quantization, typically set to 2.
float T; // A percentage value which determines when new features can be recognized as new background. (Typically 0.9).
float minArea; // Discard foreground blobs whose bounding box is smaller than this threshold.
// default Params
FGDParams();
};
CV_EXPORTS Ptr<gpu::BackgroundSubtractorFGD>
createBackgroundSubtractorFGD(const FGDParams& params = FGDParams());
}} // namespace cv { namespace gpu {
#endif /* __OPENCV_GPUBGSEGM_HPP__ */

13
modules/gpubgsegm/perf/perf_bgsegm.cpp
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@ -42,6 +42,7 @@
#include "perf_precomp.hpp"
#include "opencv2/legacy.hpp"
#include "opencv2/gpuimgproc.hpp"
using namespace std;
using namespace testing;
@ -90,10 +91,10 @@ PERF_TEST_P(Video, FGDStatModel,
if (PERF_RUN_GPU())
{
cv::gpu::GpuMat d_frame(frame);
cv::gpu::GpuMat d_frame(frame), foreground, background3, background;
cv::gpu::FGDStatModel d_model(4);
d_model.create(d_frame);
cv::Ptr<cv::gpu::BackgroundSubtractorFGD> d_fgd = cv::gpu::createBackgroundSubtractorFGD();
d_fgd->apply(d_frame, foreground);
for (int i = 0; i < 10; ++i)
{
@ -103,12 +104,12 @@ PERF_TEST_P(Video, FGDStatModel,
d_frame.upload(frame);
startTimer(); next();
d_model.update(d_frame);
d_fgd->apply(d_frame, foreground);
stopTimer();
}
const cv::gpu::GpuMat background = d_model.background;
const cv::gpu::GpuMat foreground = d_model.foreground;
d_fgd->getBackgroundImage(background3);
cv::gpu::cvtColor(background3, background, cv::COLOR_BGR2BGRA);
GPU_SANITY_CHECK(background, 1e-2, ERROR_RELATIVE);
GPU_SANITY_CHECK(foreground, 1e-2, ERROR_RELATIVE);

2
modules/gpubgsegm/src/cuda/fgd.cu
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@ -53,7 +53,7 @@
using namespace cv::gpu;
using namespace cv::gpu::cudev;
namespace bgfg
namespace fgd
{
////////////////////////////////////////////////////////////////////////////
// calcDiffHistogram

2
modules/gpubgsegm/src/cuda/fgd.hpp
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@ -45,7 +45,7 @@
#include "opencv2/core/gpu_types.hpp"
namespace bgfg
namespace fgd
{
struct BGPixelStat
{

800
modules/gpubgsegm/src/fgd.cpp
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43
modules/gpubgsegm/test/test_bgsegm.cpp
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@ -72,11 +72,10 @@ namespace cv
}
}
PARAM_TEST_CASE(FGDStatModel, cv::gpu::DeviceInfo, std::string, Channels)
PARAM_TEST_CASE(FGDStatModel, cv::gpu::DeviceInfo, std::string)
{
cv::gpu::DeviceInfo devInfo;
std::string inputFile;
int out_cn;
virtual void SetUp()
{
@ -84,8 +83,6 @@ PARAM_TEST_CASE(FGDStatModel, cv::gpu::DeviceInfo, std::string, Channels)
cv::gpu::setDevice(devInfo.deviceID());
inputFile = std::string(cvtest::TS::ptr()->get_data_path()) + "video/" + GET_PARAM(1);
out_cn = GET_PARAM(2);
}
};
@ -102,15 +99,10 @@ GPU_TEST_P(FGDStatModel, Update)
cv::Ptr<CvBGStatModel> model(cvCreateFGDStatModel(&ipl_frame));
cv::gpu::GpuMat d_frame(frame);
cv::gpu::FGDStatModel d_model(out_cn);
d_model.create(d_frame);
cv::Mat h_background;
cv::Mat h_foreground;
cv::Mat h_background3;
cv::Mat backgroundDiff;
cv::Mat foregroundDiff;
cv::Ptr<cv::gpu::BackgroundSubtractorFGD> d_fgd = cv::gpu::createBackgroundSubtractorFGD();
cv::gpu::GpuMat d_foreground, d_background;
std::vector< std::vector<cv::Point> > foreground_regions;
d_fgd->apply(d_frame, d_foreground);
for (int i = 0; i < 5; ++i)
{
@ -121,32 +113,23 @@ GPU_TEST_P(FGDStatModel, Update)
int gold_count = cvUpdateBGStatModel(&ipl_frame, model);
d_frame.upload(frame);
int count = d_model.update(d_frame);
ASSERT_EQ(gold_count, count);
d_fgd->apply(d_frame, d_foreground);
d_fgd->getBackgroundImage(d_background);
d_fgd->getForegroundRegions(foreground_regions);
int count = (int) foreground_regions.size();
cv::Mat gold_background = cv::cvarrToMat(model->background);
cv::Mat gold_foreground = cv::cvarrToMat(model->foreground);
if (out_cn == 3)
d_model.background.download(h_background3);
else
{
d_model.background.download(h_background);
cv::cvtColor(h_background, h_background3, cv::COLOR_BGRA2BGR);
}
d_model.foreground.download(h_foreground);
ASSERT_MAT_NEAR(gold_background, h_background3, 1.0);
ASSERT_MAT_NEAR(gold_foreground, h_foreground, 0.0);
ASSERT_MAT_NEAR(gold_background, d_background, 1.0);
ASSERT_MAT_NEAR(gold_foreground, d_foreground, 0.0);
ASSERT_EQ(gold_count, count);
}
}
INSTANTIATE_TEST_CASE_P(GPU_BgSegm, FGDStatModel, testing::Combine(
ALL_DEVICES,
testing::Values(std::string("768x576.avi")),
testing::Values(Channels(3), Channels(4))));
testing::Values(std::string("768x576.avi"))));
#endif

9
samples/gpu/bgfg_segm.cpp
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@ -78,7 +78,7 @@ int main(int argc, const char** argv)
Ptr<BackgroundSubtractor> mog = gpu::createBackgroundSubtractorMOG();
Ptr<BackgroundSubtractor> mog2 = gpu::createBackgroundSubtractorMOG2();
Ptr<BackgroundSubtractor> gmg = gpu::createBackgroundSubtractorGMG(40);
FGDStatModel fgd_stat;
Ptr<BackgroundSubtractor> fgd = gpu::createBackgroundSubtractorFGD();
GpuMat d_fgmask;
GpuMat d_fgimg;
@ -103,7 +103,7 @@ int main(int argc, const char** argv)
break;
case FGD_STAT:
fgd_stat.create(d_frame);
fgd->apply(d_frame, d_fgmask);
break;
}
@ -142,9 +142,8 @@ int main(int argc, const char** argv)
break;
case FGD_STAT:
fgd_stat.update(d_frame);
d_fgmask = fgd_stat.foreground;
d_bgimg = fgd_stat.background;
fgd->apply(d_frame, d_fgmask);
fgd->getBackgroundImage(d_bgimg);
break;
}

14
samples/gpu/performance/tests.cpp
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@ -1271,14 +1271,14 @@ TEST(FGDStatModel)
{
const std::string inputFile = abspath("768x576.avi");
cv::VideoCapture cap(inputFile);
VideoCapture cap(inputFile);
if (!cap.isOpened()) throw runtime_error("can't open 768x576.avi");
cv::Mat frame;
Mat frame;
cap >> frame;
IplImage ipl_frame = frame;
cv::Ptr<CvBGStatModel> model(cvCreateFGDStatModel(&ipl_frame));
Ptr<CvBGStatModel> model(cvCreateFGDStatModel(&ipl_frame));
while (!TestSystem::instance().stop())
{
@ -1297,8 +1297,10 @@ TEST(FGDStatModel)
cap >> frame;
cv::gpu::GpuMat d_frame(frame);
cv::gpu::FGDStatModel d_model(d_frame);
gpu::GpuMat d_frame(frame), d_fgmask;
Ptr<BackgroundSubtractor> d_fgd = gpu::createBackgroundSubtractorFGD();
d_fgd->apply(d_frame, d_fgmask);
while (!TestSystem::instance().stop())
{
@ -1307,7 +1309,7 @@ TEST(FGDStatModel)
TestSystem::instance().gpuOn();
d_model.update(d_frame);
d_fgd->apply(d_frame, d_fgmask);
TestSystem::instance().gpuOff();
}