--- /dev/null
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+// By downloading, copying, installing or using the software you agree to this license.
+// If you do not agree to this license, do not download, install,
+// copy or use the software.
+//
+//
+// Intel License Agreement
+//
+// Copyright (C) 2000, Intel Corporation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+// * Redistribution's of source code must retain the above copyright notice,
+// this list of conditions and the following disclaimer.
+//
+// * Redistribution's in binary form must reproduce the above copyright notice,
+// this list of conditions and the following disclaimer in the documentation
+// and/or other materials provided with the distribution.
+//
+// * The name of Intel Corporation may not be used to endorse or promote products
+// derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "_cvaux.h"
+
+#define SCALE_BASE 1.1
+#define SCALE_RANGE 2
+#define SCALE_NUM (2*SCALE_RANGE+1)
+typedef float DefHistType;
+#define DefHistTypeMat CV_32F
+#define HIST_INDEX(_pData) (((_pData)[0]>>m_ByteShift) + (((_pData)[1]>>(m_ByteShift))<<m_BinBit)+((pImgData[2]>>m_ByteShift)<<(m_BinBit*2)))
+
+void calcKernelEpanechnikov(CvMat* pK)
+{ /* Allocate kernel for histogramm creation: */
+ int x,y;
+ int w = pK->width;
+ int h = pK->height;
+ float x0 = 0.5f*(w-1);
+ float y0 = 0.5f*(h-1);
+
+ for(y=0; y<h; ++y) for(x=0; x<w; ++x)
+ {
+// float r2 = ((x-x0)*(x-x0)/(x0*x0)+(y-y0)*(y-y0)/(y0*y0));
+ float r2 = ((x-x0)*(x-x0)+(y-y0)*(y-y0))/((x0*x0)+(y0*y0));
+ CV_MAT_ELEM(pK[0],DefHistType, y, x) = (DefHistType)((r2<1)?(1-r2):0);
+ }
+} /* Allocate kernel for histogram creation. */
+
+class CvBlobTrackerOneMSFGS:public CvBlobTrackerOne
+{
+private:
+ /* Parameters: */
+ float m_FGWeight;
+ float m_Alpha;
+ CvSize m_ObjSize;
+ CvMat* m_KernelHistModel;
+ CvMat* m_KernelHistCandidate;
+ CvSize m_KernelMeanShiftSize;
+ CvMat* m_KernelMeanShiftK[SCALE_NUM];
+ CvMat* m_KernelMeanShiftG[SCALE_NUM];
+ CvMat* m_Weights;
+ int m_BinBit;
+ int m_ByteShift;
+ int m_BinNum;
+ int m_Dim;
+ int m_BinNumTotal;
+ CvMat* m_HistModel;
+ float m_HistModelVolume;
+ CvMat* m_HistCandidate;
+ float m_HistCandidateVolume;
+ CvMat* m_HistTemp;
+ CvBlob m_Blob;
+
+ void ReAllocHist(int Dim, int BinBit)
+ {
+ m_BinBit = BinBit;
+ m_ByteShift = 8-BinBit;
+ m_Dim = Dim;
+ m_BinNum = (1<<BinBit);
+ m_BinNumTotal = cvRound(pow((double)m_BinNum,(double)m_Dim));
+ if(m_HistModel) cvReleaseMat(&m_HistModel);
+ if(m_HistCandidate) cvReleaseMat(&m_HistCandidate);
+ if(m_HistTemp) cvReleaseMat(&m_HistTemp);
+ m_HistCandidate = cvCreateMat(1, m_BinNumTotal, DefHistTypeMat);
+ m_HistModel = cvCreateMat(1, m_BinNumTotal, DefHistTypeMat);
+ m_HistTemp = cvCreateMat(1, m_BinNumTotal, DefHistTypeMat);
+ cvZero(m_HistCandidate);
+ cvZero(m_HistModel);
+ m_HistModelVolume = 0.0f;
+ m_HistCandidateVolume = 0.0f;
+ }
+
+ void ReAllocKernel(int w, int h, float sigma=0.4)
+ {
+ double ScaleToObj = sigma*1.39;
+ int kernel_width = cvRound(w/ScaleToObj);
+ int kernel_height = cvRound(h/ScaleToObj);
+ int x,y,s;
+ assert(w>0);
+ assert(h>0);
+ m_ObjSize = cvSize(w,h);
+ m_KernelMeanShiftSize = cvSize(kernel_width,kernel_height);
+
+
+ /* Create kernels for histogram calculation: */
+ if(m_KernelHistModel) cvReleaseMat(&m_KernelHistModel);
+ m_KernelHistModel = cvCreateMat(h, w, DefHistTypeMat);
+ calcKernelEpanechnikov(m_KernelHistModel);
+ if(m_KernelHistCandidate) cvReleaseMat(&m_KernelHistCandidate);
+ m_KernelHistCandidate = cvCreateMat(kernel_height, kernel_width, DefHistTypeMat);
+ calcKernelEpanechnikov(m_KernelHistCandidate);
+
+ if(m_Weights) cvReleaseMat(&m_Weights);
+ m_Weights = cvCreateMat(kernel_height, kernel_width, CV_32F);
+
+ for(s=-SCALE_RANGE; s<=SCALE_RANGE; ++s)
+ { /* Allocate kernel for meanshifts in space and scale: */
+ int si = s+SCALE_RANGE;
+ double cur_sigma = sigma * pow(SCALE_BASE,s);
+ double cur_sigma2 = cur_sigma*cur_sigma;
+ double x0 = 0.5*(kernel_width-1);
+ double y0 = 0.5*(kernel_height-1);
+ if(m_KernelMeanShiftK[si]) cvReleaseMat(&m_KernelMeanShiftK[si]);
+ if(m_KernelMeanShiftG[si]) cvReleaseMat(&m_KernelMeanShiftG[si]);
+ m_KernelMeanShiftK[si] = cvCreateMat(kernel_height, kernel_width, DefHistTypeMat);
+ m_KernelMeanShiftG[si] = cvCreateMat(kernel_height, kernel_width, DefHistTypeMat);
+
+ for(y=0; y<kernel_height; ++y)
+ {
+ DefHistType* pK = (DefHistType*)CV_MAT_ELEM_PTR_FAST( m_KernelMeanShiftK[si][0], y, 0, sizeof(DefHistType) );
+ DefHistType* pG = (DefHistType*)CV_MAT_ELEM_PTR_FAST( m_KernelMeanShiftG[si][0], y, 0, sizeof(DefHistType) );
+
+ for(x=0; x<kernel_width; ++x)
+ {
+ double r2 = ((x-x0)*(x-x0)/(x0*x0)+(y-y0)*(y-y0)/(y0*y0));
+ double sigma12 = cur_sigma2 / 2.56;
+ double sigma22 = cur_sigma2 * 2.56;
+ pK[x] = (DefHistType)(Gaussian2D(r2, sigma12)/sigma12 - Gaussian2D(r2, sigma22)/sigma22);
+ pG[x] = (DefHistType)(Gaussian2D(r2, cur_sigma2/1.6) - Gaussian2D(r2, cur_sigma2*1.6));
+ }
+ } /* Next line. */
+ }
+ } /* ReallocKernel */
+
+ inline double Gaussian2D(double x, double sigma2)
+ {
+ return (exp(-x/(2*sigma2)) / (2*3.1415926535897932384626433832795*sigma2) );
+ }
+
+ void calcHist(IplImage* pImg, IplImage* pMask, CvPoint Center, CvMat* pKernel, CvMat* pHist, DefHistType* pHistVolume)
+ {
+ int w = pKernel->width;
+ int h = pKernel->height;
+ DefHistType Volume = 0;
+ int x0 = Center.x - w/2;
+ int y0 = Center.y - h/2;
+ int x,y;
+
+ //cvZero(pHist);
+ cvSet(pHist,cvScalar(1.0/m_BinNumTotal)); /* no zero bins, all bins have very small value*/
+ Volume = 1;
+
+ if(m_Dim == 3)
+ {
+ for(y=0; y<h; ++y)
+ {
+ unsigned char* pImgData = NULL;
+ unsigned char* pMaskData = NULL;
+ DefHistType* pKernelData = NULL;
+ if((y0+y)>=pImg->height) continue;
+ if((y0+y)<0)continue;
+ pImgData = &CV_IMAGE_ELEM(pImg,unsigned char,y+y0,x0*3);
+ pMaskData = pMask?(&CV_IMAGE_ELEM(pMask,unsigned char,y+y0,x0)):NULL;
+ pKernelData = (DefHistType*)CV_MAT_ELEM_PTR_FAST(pKernel[0],y,0,sizeof(DefHistType));
+
+ for(x=0; x<w; ++x, pImgData+=3)
+ {
+ if((x0+x)>=pImg->width) continue;
+ if((x0+x)<0)continue;
+
+ if(pMaskData==NULL || pMaskData[x]>128)
+ {
+ DefHistType K = pKernelData[x];
+ int index = HIST_INDEX(pImgData);
+ assert(index >= 0 && index < pHist->cols);
+ Volume += K;
+ ((DefHistType*)(pHist->data.ptr))[index] += K;
+
+ } /* Only masked pixels. */
+ } /* Next column. */
+ } /* Next row. */
+ } /* if m_Dim == 3. */
+
+ if(pHistVolume)pHistVolume[0] = Volume;
+
+ }; /* calcHist */
+
+ double calcBhattacharyya()
+ {
+ cvMul(m_HistCandidate,m_HistModel,m_HistTemp);
+ cvPow(m_HistTemp,m_HistTemp,0.5);
+ return cvSum(m_HistTemp).val[0] / sqrt(m_HistCandidateVolume*m_HistModelVolume);
+ } /* calcBhattacharyyaCoefficient */
+
+ void calcWeights(IplImage* pImg, IplImage* pImgFG, CvPoint Center)
+ {
+ cvZero(m_Weights);
+
+ /* Calculate new position: */
+ if(m_Dim == 3)
+ {
+ int x0 = Center.x - m_KernelMeanShiftSize.width/2;
+ int y0 = Center.y - m_KernelMeanShiftSize.height/2;
+ int x,y;
+
+ assert(m_Weights->width == m_KernelMeanShiftSize.width);
+ assert(m_Weights->height == m_KernelMeanShiftSize.height);
+
+ /* Calcualte shift vector: */
+ for(y=0; y<m_KernelMeanShiftSize.height; ++y)
+ {
+ unsigned char* pImgData = NULL;
+ unsigned char* pMaskData = NULL;
+ float* pWData = NULL;
+
+ if(y+y0 < 0 || y+y0 >= pImg->height) continue;
+
+ pImgData = &CV_IMAGE_ELEM(pImg,unsigned char,y+y0,x0*3);
+ pMaskData = pImgFG?(&CV_IMAGE_ELEM(pImgFG,unsigned char,y+y0,x0)):NULL;
+ pWData = (float*)CV_MAT_ELEM_PTR_FAST(m_Weights[0],y,0,sizeof(float));
+
+ for(x=0; x<m_KernelMeanShiftSize.width; ++x, pImgData+=3)
+ {
+ double V = 0;
+ double HM = 0;
+ double HC = 0;
+ int index;
+ if(x+x0 < 0 || x+x0 >= pImg->width) continue;
+
+ index = HIST_INDEX(pImgData);
+ assert(index >= 0 && index < m_BinNumTotal);
+
+ if(m_HistModelVolume>0)
+ HM = ((DefHistType*)m_HistModel->data.ptr)[index]/m_HistModelVolume;
+
+ if(m_HistCandidateVolume>0)
+ HC = ((DefHistType*)m_HistCandidate->data.ptr)[index]/m_HistCandidateVolume;
+
+ V = (HC>0)?sqrt(HM / HC):0;
+ V += m_FGWeight*(pMaskData?((pMaskData[x]/255.0f)):0);
+ pWData[x] = (float)MIN(V,100000);
+
+ } /* Next column. */
+ } /* Next row. */
+ } /* if m_Dim == 3. */
+ } /* calcWeights */
+
+public:
+ CvBlobTrackerOneMSFGS()
+ {
+ int i;
+ m_FGWeight = 0;
+ m_Alpha = 0.0;
+
+ /* Add several parameters for external use: */
+ AddParam("FGWeight", &m_FGWeight);
+ CommentParam("FGWeight","Weight of FG mask using (0 - mask will not be used for tracking)");
+ AddParam("Alpha", &m_Alpha);
+ CommentParam("Alpha","Coefficient for model histogramm updating (0 - hist is not upated)");
+
+ m_BinBit=0;
+ m_Dim = 0;
+ m_HistModel = NULL;
+ m_HistCandidate = NULL;
+ m_HistTemp = NULL;
+ m_KernelHistModel = NULL;
+ m_KernelHistCandidate = NULL;
+ m_Weights = NULL;
+
+ for(i=0; i<SCALE_NUM; ++i)
+ {
+ m_KernelMeanShiftK[i] = NULL;
+ m_KernelMeanShiftG[i] = NULL;
+ }
+ ReAllocHist(3,5); /* 3D hist, each dimension has 2^5 bins. */
+
+ SetModuleName("MSFGS");
+ }
+
+ ~CvBlobTrackerOneMSFGS()
+ {
+ int i;
+ if(m_HistModel) cvReleaseMat(&m_HistModel);
+ if(m_HistCandidate) cvReleaseMat(&m_HistCandidate);
+ if(m_HistTemp) cvReleaseMat(&m_HistTemp);
+ if(m_KernelHistModel) cvReleaseMat(&m_KernelHistModel);
+
+ for(i=0; i<SCALE_NUM; ++i)
+ {
+ if(m_KernelMeanShiftK[i]) cvReleaseMat(&m_KernelMeanShiftK[i]);
+ if(m_KernelMeanShiftG[i]) cvReleaseMat(&m_KernelMeanShiftG[i]);
+ }
+ }
+
+ /* Interface: */
+ virtual void Init(CvBlob* pBlobInit, IplImage* pImg, IplImage* pImgFG = NULL)
+ {
+ int w = cvRound(CV_BLOB_WX(pBlobInit));
+ int h = cvRound(CV_BLOB_WY(pBlobInit));
+ if(w<3)w=3;
+ if(h<3)h=3;
+ if(w>pImg->width)w=pImg->width;
+ if(h>pImg->height)h=pImg->height;
+ ReAllocKernel(w,h);
+ calcHist(pImg, pImgFG, cvPointFrom32f(CV_BLOB_CENTER(pBlobInit)), m_KernelHistModel, m_HistModel, &m_HistModelVolume);
+ m_Blob = pBlobInit[0];
+ };
+
+ virtual CvBlob* Process(CvBlob* pBlobPrev, IplImage* pImg, IplImage* pImgFG = NULL)
+ {
+ int iter;
+
+ if(pBlobPrev)
+ {
+ m_Blob = pBlobPrev[0];
+ }
+
+ for(iter=0; iter<10; ++iter)
+ {
+// float newx=0,newy=0,sum=0;
+ float dx=0,dy=0,sum=0;
+ int x,y,si;
+
+ CvPoint Center = cvPoint(cvRound(m_Blob.x),cvRound(m_Blob.y));
+ CvSize Size = cvSize(cvRound(m_Blob.w),cvRound(m_Blob.h));
+
+ if(m_ObjSize.width != Size.width || m_ObjSize.height != Size.height)
+ { /* Reallocate kernels: */
+ ReAllocKernel(Size.width,Size.height);
+ } /* Reallocate kernels. */
+
+ /* Mean shift in coordinate space: */
+ calcHist(pImg, NULL, Center, m_KernelHistCandidate, m_HistCandidate, &m_HistCandidateVolume);
+ calcWeights(pImg, pImgFG, Center);
+
+ for(si=1; si<(SCALE_NUM-1); ++si)
+ {
+ CvMat* pKernel = m_KernelMeanShiftK[si];
+ float sdx = 0, sdy=0, ssum=0;
+ int s = si-SCALE_RANGE;
+ float factor = (1.0f-( float(s)/float(SCALE_RANGE) )*( float(s)/float(SCALE_RANGE) ));
+
+ for(y=0; y<m_KernelMeanShiftSize.height; ++y)
+ for(x=0; x<m_KernelMeanShiftSize.width; ++x)
+ {
+ float W = *(float*)CV_MAT_ELEM_PTR_FAST(m_Weights[0],y,x,sizeof(float));
+ float K = *(float*)CV_MAT_ELEM_PTR_FAST(pKernel[0],y,x,sizeof(float));
+ float KW = K*W;
+ ssum += (float)fabs(KW);
+ sdx += KW*(x-m_KernelMeanShiftSize.width*0.5f);
+ sdy += KW*(y-m_KernelMeanShiftSize.height*0.5f);
+ } /* Next pixel. */
+
+ dx += sdx * factor;
+ dy += sdy * factor;
+ sum += ssum * factor;
+
+ } /* Next scale. */
+
+ if(sum > 0)
+ {
+ dx /= sum;
+ dy /= sum;
+ }
+
+ m_Blob.x += dx;
+ m_Blob.y += dy;
+
+ { /* Mean shift in scale space: */
+ float news = 0;
+ float sum = 0;
+ float scale;
+
+ Center = cvPoint(cvRound(m_Blob.x),cvRound(m_Blob.y));
+ calcHist(pImg, NULL, Center, m_KernelHistCandidate, m_HistCandidate, &m_HistCandidateVolume);
+ calcWeights(pImg, pImgFG, Center);
+ //cvSet(m_Weights,cvScalar(1));
+
+ for(si=0; si<SCALE_NUM; si++)
+ {
+ double W = cvDotProduct(m_Weights, m_KernelMeanShiftG[si]);;
+ int s = si-SCALE_RANGE;
+ sum += (float)fabs(W);
+ news += (float)(s*W);
+ }
+
+ if(sum>0)
+ {
+ news /= sum;
+ }
+
+ scale = (float)pow((double)SCALE_BASE,(double)news);
+ m_Blob.w *= scale;
+ m_Blob.h *= scale;
+ } /* Mean shift in scale space. */
+
+ /* Check fo finish: */
+ if(fabs(dx)<0.1 && fabs(dy)<0.1) break;
+
+ } /* Next iteration. */
+
+ if(m_Alpha>0)
+ { /* Update histogram: */
+ double Vol, WM, WC;
+ CvPoint Center = cvPoint(cvRound(m_Blob.x),cvRound(m_Blob.y));
+ calcHist(pImg, pImgFG, Center, m_KernelHistModel, m_HistCandidate, &m_HistCandidateVolume);
+ Vol = 0.5*(m_HistModelVolume + m_HistCandidateVolume);
+ WM = Vol*(1-m_Alpha)/m_HistModelVolume;
+ WC = Vol*(m_Alpha)/m_HistCandidateVolume;
+ cvAddWeighted(m_HistModel, WM, m_HistCandidate,WC,0,m_HistModel);
+ m_HistModelVolume = (float)cvSum(m_HistModel).val[0];
+ } /* Update histogram. */
+
+ return &m_Blob;
+
+ }; /* Process */
+
+ virtual void Release(){delete this;};
+}; /*CvBlobTrackerOneMSFGS*/
+
+CvBlobTrackerOne* cvCreateBlobTrackerOneMSFGS()
+{
+ return (CvBlobTrackerOne*) new CvBlobTrackerOneMSFGS;
+}
+
+CvBlobTracker* cvCreateBlobTrackerMSFGS()
+{
+ return cvCreateBlobTrackerList(cvCreateBlobTrackerOneMSFGS);
+}
+
projects / opencv / blobdiff