/*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 "precomp.hpp" #ifdef _OPENMP #include "omp.h" #endif // Uncomment to trade flexibility for speed //#define CONST_HIST_SIZE // Uncomment to get some performance stats in stderr //#define REPORT_TICKS #ifdef CONST_HIST_SIZE #define m_BinBit 5 #define m_ByteShift 3 #endif typedef float DefHistType; #define DefHistTypeMat CV_32F #define HIST_INDEX(_pData) (((_pData)[0]>>m_ByteShift) + (((_pData)[1]>>(m_ByteShift))<>m_ByteShift)<<(m_BinBit*2))) class DefHist { public: CvMat* m_pHist; DefHistType m_HistVolume; DefHist(int BinNum=0) { m_pHist = NULL; m_HistVolume = 0; Resize(BinNum); } ~DefHist() { if(m_pHist)cvReleaseMat(&m_pHist); } void Resize(int BinNum) { if(m_pHist)cvReleaseMat(&m_pHist); if(BinNum>0) { m_pHist = cvCreateMat(1, BinNum, DefHistTypeMat); cvZero(m_pHist); } m_HistVolume = 0; } void Update(DefHist* pH, float W) { /* Update histogram: */ double Vol, WM, WC; Vol = 0.5*(m_HistVolume + pH->m_HistVolume); WM = Vol*(1-W)/m_HistVolume; WC = Vol*(W)/pH->m_HistVolume; cvAddWeighted(m_pHist, WM, pH->m_pHist,WC,0,m_pHist); m_HistVolume = (float)cvSum(m_pHist).val[0]; } /* Update histogram: */ }; class CvBlobTrackerOneMSFG:public CvBlobTrackerOne { protected: int m_BinNumTotal; /* protected only for parralel MSPF */ CvSize m_ObjSize; void ReAllocKernel(int w, int h) { int x,y; float x0 = 0.5f*(w-1); float y0 = 0.5f*(h-1); assert(w>0); assert(h>0); m_ObjSize = cvSize(w,h); if(m_KernelHist) cvReleaseMat(&m_KernelHist); if(m_KernelMeanShift) cvReleaseMat(&m_KernelMeanShift); m_KernelHist = cvCreateMat(h, w, DefHistTypeMat); m_KernelMeanShift = cvCreateMat(h, w, DefHistTypeMat); for(y=0; yw); int BH = cvRound(pBlob->h); DefHistType Volume = 0; int x0 = cvRound(pBlob->x - BW*0.5); int y0 = cvRound(pBlob->y - BH*0.5); int x,y; UsePrecalculatedKernel = (BW == m_ObjSize.width && BH == m_ObjSize.height ) ; //cvZero(pHist); cvSet(pHist->m_pHist,cvScalar(1.0/m_BinNumTotal)); /* no zero bins, all bins have very small value*/ Volume = 1; assert(BW < pImg->width); assert(BH < pImg->height); if((x0+BW)>=pImg->width) BW=pImg->width-x0-1; if((y0+BH)>=pImg->height) BH=pImg->height-y0-1; if(x0<0){ x0=0;} if(y0<0){ y0=0;} if(m_Dim == 3) { for(y=0; y= 0 && index < pHist->m_pHist->cols); if(UsePrecalculatedKernel) { K = pKernelData[x]; } else { float dx = (x+x0-pBlob->x)/(pBlob->w*0.5f); float dy = (y+y0-pBlob->y)/(pBlob->h*0.5f); double r2 = dx*dx+dy*dy; K = (float)GetKernelHist(r2); } if(pMaskData) { K *= pMaskData[x]*0.003921568627450980392156862745098f; } Volume += K; ((DefHistType*)(pHist->m_pHist->data.ptr))[index] += K; } /* Next column. */ } /* Next row. */ } /* if m_Dim == 3. */ pHist->m_HistVolume = Volume; }; /* CollectHist */ double calcBhattacharyya(DefHist* pHM = NULL, DefHist* pHC = NULL, DefHist* pHT = NULL) { if(pHM==NULL) pHM = &m_HistModel; if(pHC==NULL) pHC = &m_HistCandidate; if(pHT==NULL) pHT = &m_HistTemp; if(pHC->m_HistVolume*pHM->m_HistVolume > 0) { #if 0 // Use CV functions: cvMul(pHM->m_pHist,pHC->m_pHist,pHT->m_pHist); cvPow(pHT->m_pHist,pHT->m_pHist,0.5); return cvSum(pHT->m_pHist).val[0] / sqrt(pHC->m_HistVolume*pHM->m_HistVolume); #else // Do computations manually and let autovectorizer do the job: DefHistType* hm=(DefHistType *)(pHM->m_pHist->data.ptr); DefHistType* hc=(DefHistType *)(pHC->m_pHist->data.ptr); //ht=(DefHistType *)(pHT->m_pHist->data.ptr); int size = pHM->m_pHist->width*pHM->m_pHist->height; double sum = 0.; for(int i = 0; i < size; i++ ) { sum += sqrt(hm[i]*hc[i]); } return sum / sqrt(pHC->m_HistVolume*pHM->m_HistVolume); #endif } return 0; } /* calcBhattacharyyaCoefficient. */ protected: // double GetBhattacharyya(IplImage* pImg, IplImage* pImgFG, float x, float y, DefHist* pHist=NULL) double GetBhattacharyya(IplImage* pImg, IplImage* pImgFG, CvBlob* pBlob, DefHist* pHist=NULL, int /*thread_number*/ = 0) { if(pHist==NULL)pHist = &m_HistTemp; CollectHist(pImg, pImgFG, pBlob, pHist); return calcBhattacharyya(&m_HistModel, pHist, pHist); } void UpdateModelHist(IplImage* pImg, IplImage* pImgFG, CvBlob* pBlob) { if(m_Alpha>0 && !m_Collision) { /* Update histogram: */ CollectHist(pImg, pImgFG, pBlob, &m_HistCandidate); m_HistModel.Update(&m_HistCandidate, m_Alpha); } /* Update histogram. */ } /* UpdateModelHist */ public: CvBlobTrackerOneMSFG() { /* Add several parameters for external use: */ m_FGWeight = 2; AddParam("FGWeight", &m_FGWeight); CommentParam("FGWeight","Weight of FG mask using (0 - mask will not be used for tracking)"); m_Alpha = 0.01f; AddParam("Alpha", &m_Alpha); CommentParam("Alpha","Coefficient for model histogram updating (0 - hist is not upated)"); m_IterNum = 10; AddParam("IterNum", &m_IterNum); CommentParam("IterNum","Maximal number of iteration in meanshift operation"); /* Initialize internal data: */ m_Collision = 0; // m_BinBit=0; m_Dim = 0; /* m_HistModel = NULL; m_HistCandidate = NULL; m_HistTemp = NULL; */ m_KernelHist = NULL; m_KernelMeanShift = NULL; ReAllocHist(3,5); /* 3D hist, each dim has 2^5 bins*/ SetModuleName("MSFG"); } ~CvBlobTrackerOneMSFG() { /* if(m_HistModel) cvReleaseMat(&m_HistModel); if(m_HistCandidate) cvReleaseMat(&m_HistCandidate); if(m_HistTemp) cvReleaseMat(&m_HistTemp); */ if(m_KernelHist) cvReleaseMat(&m_KernelHist); if(m_KernelMeanShift) cvReleaseMat(&m_KernelMeanShift); } /* 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(wpImg->width)w=pImg->width; if(h>pImg->height)h=pImg->height; } ReAllocKernel(w,h); if(pImg) CollectHist(pImg, pImgFG, pBlobInit, &m_HistModel); m_Blob = pBlobInit[0]; }; virtual CvBlob* Process(CvBlob* pBlobPrev, IplImage* pImg, IplImage* pImgFG = NULL) { int iter; if(pBlobPrev) { m_Blob = pBlobPrev[0]; } { /* Check blob size and realloc kernels if it is necessary: */ int w = cvRound(m_Blob.w); int h = cvRound(m_Blob.h); if( w != m_ObjSize.width || h!=m_ObjSize.height) { ReAllocKernel(w,h); /* after this ( w != m_ObjSize.width || h!=m_ObjSize.height) shoiuld be false */ } } /* Check blob size and realloc kernels if it is necessary: */ for(iter=0; iterwidth); assert(m_ObjSize.height < pImg->height); /* Calculate shift vector: */ for(y=0; yheight; ++y) { unsigned char* pImgData = &CV_IMAGE_ELEM(pImg,unsigned char,y,0); unsigned char* pMaskData = pImgFG?(&CV_IMAGE_ELEM(pImgFG,unsigned char,y,0)):NULL; for(x=0; xwidth; ++x, pImgData+=3) { int xk = cvRound(x-(m_Blob.x-m_Blob.w*0.5)); int yk = cvRound(y-(m_Blob.y-m_Blob.h*0.5)); double HM = 0; double HC = 0; double K; int index = HIST_INDEX(pImgData); assert(index >= 0 && index < m_BinNumTotal); if(fabs(x-m_Blob.x)>m_Blob.w*0.6) continue; if(fabs(y-m_Blob.y)>m_Blob.h*0.6) continue; if(xk < 0 || xk >= m_KernelMeanShift->cols) continue; if(yk < 0 || yk >= m_KernelMeanShift->rows) continue; if(m_HistModel.m_HistVolume>0) HM = ((DefHistType*)m_HistModel.m_pHist->data.ptr)[index]/m_HistModel.m_HistVolume; if(m_HistCandidate.m_HistVolume>0) HC = ((DefHistType*)m_HistCandidate.m_pHist->data.ptr)[index]/m_HistCandidate.m_HistVolume; K = *(DefHistType*)CV_MAT_ELEM_PTR_FAST(m_KernelMeanShift[0],yk,xk,sizeof(DefHistType)); if(HC>0) { double V = sqrt(HM / HC); int Vi = cvRound(V * 64); if(Vi < 0) Vi = 0; if(Vi > 255) Vi = 255; CV_IMAGE_ELEM(pW,uchar,y,x) = (uchar)Vi; V += m_FGWeight*(pMaskData?(pMaskData[x]/255.0f):0); V*=K; Vi = cvRound(V * 64); if(Vi < 0) Vi = 0; if(Vi > 255) Vi = 255; CV_IMAGE_ELEM(pWFG,uchar,y,x) = (uchar)Vi; } } /* Next column. */ } /* Next row. */ //cvNamedWindow("MSFG_W",0); //cvShowImage("MSFG_W",pW); //cvNamedWindow("MSFG_WFG",0); //cvShowImage("MSFG_WFG",pWFG); //cvNamedWindow("MSFG_FG",0); //cvShowImage("MSFG_FG",pImgFG); //cvSaveImage("MSFG_W.bmp",pW); //cvSaveImage("MSFG_WFG.bmp",pWFG); //cvSaveImage("MSFG_FG.bmp",pImgFG); } /* Debug. */ /* Calculate new position by meanshift: */ /* Calculate new position: */ if(m_Dim == 3) { int x0 = cvRound(m_Blob.x - m_ObjSize.width*0.5); int y0 = cvRound(m_Blob.y - m_ObjSize.height*0.5); int x,y; assert(m_ObjSize.width < pImg->width); assert(m_ObjSize.height < pImg->height); /* Crop blob bounds: */ if((x0+m_ObjSize.width)>=pImg->width) x0=pImg->width-m_ObjSize.width-1; if((y0+m_ObjSize.height)>=pImg->height) y0=pImg->height-m_ObjSize.height-1; if(x0<0){ x0=0;} if(y0<0){ y0=0;} /* Calculate shift vector: */ for(y=0; y= 0 && index < m_BinNumTotal); if(m_HistModel.m_HistVolume>0) HM = ((DefHistType*)m_HistModel.m_pHist->data.ptr)[index]/m_HistModel.m_HistVolume; if(m_HistCandidate.m_HistVolume>0) HC = ((DefHistType*)m_HistCandidate.m_pHist->data.ptr)[index]/m_HistCandidate.m_HistVolume; if(HC>0) { double V = sqrt(HM / HC); if(!m_Collision && m_FGWeight>0 && pMaskData) { V += m_FGWeight*(pMaskData[x]/255.0f); } K *= (float)MIN(V,100000.); } sum += K; newx += K*x; newy += K*y; } /* Next column. */ } /* Next row. */ if(sum > 0) { newx /= sum; newy /= sum; } newx += x0; newy += y0; } /* if m_Dim == 3. */ /* Calculate new position by meanshift: */ for(;;) { /* Iterate using bahattcharrya coefficient: */ double B1; CvBlob B = m_Blob; // CvPoint NewCenter = cvPoint(cvRound(newx),cvRound(newy)); B.x = newx; B.y = newy; CollectHist(pImg, NULL, &B, &m_HistCandidate); B1 = calcBhattacharyya(); if(B1 > B0) break; newx = 0.5f*(newx+m_Blob.x); newy = 0.5f*(newy+m_Blob.y); if(fabs(newx-m_Blob.x)<0.1 && fabs(newy-m_Blob.y)<0.1) break; } /* Iterate using bahattcharrya coefficient. */ if(fabs(newx-m_Blob.x)<0.5 && fabs(newy-m_Blob.y)<0.5) break; m_Blob.x = newx; m_Blob.y = newy; } /* Next iteration. */ while(!m_Collision && m_FGWeight>0) { /* Update size if no collision. */ float Alpha = 0.04f; CvBlob NewBlob; double M00,X,Y,XX,YY; CvMoments m; CvRect r; CvMat mat; r.width = cvRound(m_Blob.w*1.5+0.5); r.height = cvRound(m_Blob.h*1.5+0.5); r.x = cvRound(m_Blob.x - 0.5*r.width); r.y = cvRound(m_Blob.y - 0.5*r.height); if(r.x < 0) break; if(r.y < 0) break; if(r.x+r.width >= pImgFG->width) break; if(r.y+r.height >= pImgFG->height) break; if(r.height < 5 || r.width < 5) break; cvMoments( cvGetSubRect(pImgFG,&mat,r), &m, 0 ); M00 = cvGetSpatialMoment( &m, 0, 0 ); if(M00 <= 0 ) break; X = cvGetSpatialMoment( &m, 1, 0 )/M00; Y = cvGetSpatialMoment( &m, 0, 1 )/M00; XX = (cvGetSpatialMoment( &m, 2, 0 )/M00) - X*X; YY = (cvGetSpatialMoment( &m, 0, 2 )/M00) - Y*Y; NewBlob = cvBlob(r.x+(float)X,r.y+(float)Y,(float)(4*sqrt(XX)),(float)(4*sqrt(YY))); NewBlob.w = Alpha*NewBlob.w+m_Blob.w*(1-Alpha); NewBlob.h = Alpha*NewBlob.h+m_Blob.h*(1-Alpha); m_Blob.w = MAX(NewBlob.w,5); m_Blob.h = MAX(NewBlob.h,5); break; } /* Update size if no collision. */ return &m_Blob; }; /* CvBlobTrackerOneMSFG::Process */ virtual double GetConfidence(CvBlob* pBlob, IplImage* pImg, IplImage* /*pImgFG*/ = NULL, IplImage* pImgUnusedReg = NULL) { double S = 0.2; double B = GetBhattacharyya(pImg, pImgUnusedReg, pBlob, &m_HistTemp); return exp((B-1)/(2*S)); }; /*CvBlobTrackerOneMSFG::*/ virtual void Update(CvBlob* pBlob, IplImage* pImg, IplImage* pImgFG = NULL) { /* Update histogram: */ UpdateModelHist(pImg, pImgFG, pBlob?pBlob:&m_Blob); } /*CvBlobTrackerOneMSFG::*/ virtual void Release(){delete this;}; virtual void SetCollision(int CollisionFlag) { m_Collision = CollisionFlag; } virtual void SaveState(CvFileStorage* fs) { cvWriteStruct(fs, "Blob", &m_Blob, "ffffi"); cvWriteInt(fs,"Collision", m_Collision); cvWriteInt(fs,"HistVolume", cvRound(m_HistModel.m_HistVolume)); cvWrite(fs,"Hist", m_HistModel.m_pHist); }; virtual void LoadState(CvFileStorage* fs, CvFileNode* node) { CvMat* pM; cvReadStructByName(fs, node, "Blob",&m_Blob, "ffffi"); m_Collision = cvReadIntByName(fs,node,"Collision",m_Collision); pM = (CvMat*)cvRead(fs,cvGetFileNodeByName(fs,node,"Hist")); if(pM) { m_HistModel.m_pHist = pM; m_HistModel.m_HistVolume = (float)cvSum(pM).val[0]; } }; }; /*CvBlobTrackerOneMSFG*/ #if 0 void CvBlobTrackerOneMSFG::CollectHist(IplImage* pImg, IplImage* pMask, CvBlob* pBlob, DefHist* pHist) { int UsePrecalculatedKernel = 0; int BW = cvRound(pBlob->w); int BH = cvRound(pBlob->h); DefHistType Volume = 0; int x0 = cvRound(pBlob->x - BW*0.5); int y0 = cvRound(pBlob->y - BH*0.5); int x,y; UsePrecalculatedKernel = (BW == m_ObjSize.width && BH == m_ObjSize.height ) ; //cvZero(pHist); cvSet(pHist->m_pHist,cvScalar(1.0/m_BinNumTotal)); /* no zero bins, all bins have very small value*/ Volume = 1; assert(BW < pImg->width); assert(BH < pImg->height); if((x0+BW)>=pImg->width) BW=pImg->width-x0-1; if((y0+BH)>=pImg->height) BH=pImg->height-y0-1; if(x0<0){ x0=0;} if(y0<0){ y0=0;} if(m_Dim == 3) { for(y=0; y= 0 && index < pHist->m_pHist->cols); if(UsePrecalculatedKernel) { K = pKernelData[x]; } else { float dx = (x+x0-pBlob->x)/(pBlob->w*0.5); float dy = (y+y0-pBlob->y)/(pBlob->h*0.5); double r2 = dx*dx+dy*dy; K = GetKernelHist(r2); } if(pMaskData) { K *= pMaskData[x]*0.003921568627450980392156862745098; } Volume += K; ((DefHistType*)(pHist->m_pHist->data.ptr))[index] += K; } /* Next column. */ } /* Next row. */ } /* if m_Dim == 3. */ pHist->m_HistVolume = Volume; }; /* CollectHist */ #endif CvBlobTrackerOne* cvCreateBlobTrackerOneMSFG() { return (CvBlobTrackerOne*) new CvBlobTrackerOneMSFG; } CvBlobTracker* cvCreateBlobTrackerMSFG() { return cvCreateBlobTrackerList(cvCreateBlobTrackerOneMSFG); } /* Create specific tracker without FG * usin - just simple mean-shift tracker: */ class CvBlobTrackerOneMS:public CvBlobTrackerOneMSFG { public: CvBlobTrackerOneMS() { SetParam("FGWeight",0); DelParam("FGWeight"); SetModuleName("MS"); }; }; CvBlobTrackerOne* cvCreateBlobTrackerOneMS() { return (CvBlobTrackerOne*) new CvBlobTrackerOneMS; } CvBlobTracker* cvCreateBlobTrackerMS() { return cvCreateBlobTrackerList(cvCreateBlobTrackerOneMS); } typedef struct DefParticle { CvBlob blob; float Vx,Vy; double W; } DefParticle; class CvBlobTrackerOneMSPF:public CvBlobTrackerOneMS { private: /* parameters */ int m_ParticleNum; float m_UseVel; float m_SizeVar; float m_PosVar; CvSize m_ImgSize; CvBlob m_Blob; DefParticle* m_pParticlesPredicted; DefParticle* m_pParticlesResampled; CvRNG m_RNG; #ifdef _OPENMP int m_ThreadNum; DefHist* m_HistForParalel; #endif public: virtual void SaveState(CvFileStorage* fs) { CvBlobTrackerOneMS::SaveState(fs); cvWriteInt(fs,"ParticleNum",m_ParticleNum); cvWriteStruct(fs,"ParticlesPredicted",m_pParticlesPredicted,"ffffiffd",m_ParticleNum); cvWriteStruct(fs,"ParticlesResampled",m_pParticlesResampled,"ffffiffd",m_ParticleNum); }; virtual void LoadState(CvFileStorage* fs, CvFileNode* node) { //CvMat* pM; CvBlobTrackerOneMS::LoadState(fs,node); m_ParticleNum = cvReadIntByName(fs,node,"ParticleNum",m_ParticleNum); if(m_ParticleNum>0) { Realloc(); printf("sizeof(DefParticle) is %d\n", (int)sizeof(DefParticle)); cvReadStructByName(fs,node,"ParticlesPredicted",m_pParticlesPredicted,"ffffiffd"); cvReadStructByName(fs,node,"ParticlesResampled",m_pParticlesResampled,"ffffiffd"); } }; CvBlobTrackerOneMSPF() { m_pParticlesPredicted = NULL; m_pParticlesResampled = NULL; m_ParticleNum = 200; AddParam("ParticleNum",&m_ParticleNum); CommentParam("ParticleNum","Number of particles"); Realloc(); m_UseVel = 0; AddParam("UseVel",&m_UseVel); CommentParam("UseVel","Percent of particles which use velocity feature"); m_SizeVar = 0.05f; AddParam("SizeVar",&m_SizeVar); CommentParam("SizeVar","Size variation (in object size)"); m_PosVar = 0.2f; AddParam("PosVar",&m_PosVar); CommentParam("PosVar","Position variation (in object size)"); m_RNG = cvRNG(0); SetModuleName("MSPF"); #ifdef _OPENMP { m_ThreadNum = omp_get_num_procs(); m_HistForParalel = new DefHist[m_ThreadNum]; } #endif } ~CvBlobTrackerOneMSPF() { if(m_pParticlesResampled)cvFree(&m_pParticlesResampled); if(m_pParticlesPredicted)cvFree(&m_pParticlesPredicted); #ifdef _OPENMP if(m_HistForParalel) delete[] m_HistForParalel; #endif } private: void Realloc() { if(m_pParticlesResampled)cvFree(&m_pParticlesResampled); if(m_pParticlesPredicted)cvFree(&m_pParticlesPredicted); m_pParticlesPredicted = (DefParticle*)cvAlloc(sizeof(DefParticle)*m_ParticleNum); m_pParticlesResampled = (DefParticle*)cvAlloc(sizeof(DefParticle)*m_ParticleNum); }; /* Realloc*/ void DrawDebug(IplImage* pImg, IplImage* /*pImgFG*/) { int k; for(k=0; k<2; ++k) { DefParticle* pBP = k?m_pParticlesResampled:m_pParticlesPredicted; //const char* name = k?"MSPF resampled particle":"MSPF Predicted particle"; IplImage* pI = cvCloneImage(pImg); int h,hN = m_ParticleNum; CvBlob C = cvBlob(0,0,0,0); double WS = 0; for(h=0; hx; C.y += pB->y; C.w += pB->w; C.h += pB->h; WS+=W; s = cvSize(1,1); cvEllipse( pI, cvPointFrom32f(CV_BLOB_CENTER(pB)), s, 0, 0, 360, CV_RGB(CW,0,0), 1 ); } /* Next hypothesis. */ C.x /= hN; C.y /= hN; C.w /= hN; C.h /= hN; cvEllipse( pI, cvPointFrom32f(CV_BLOB_CENTER(&C)), cvSize(cvRound(C.w*0.5),cvRound(C.h*0.5)), 0, 0, 360, CV_RGB(0,0,255), 1 ); cvEllipse( pI, cvPointFrom32f(CV_BLOB_CENTER(&m_Blob)), cvSize(cvRound(m_Blob.w*0.5),cvRound(m_Blob.h*0.5)), 0, 0, 360, CV_RGB(0,255,0), 1 ); //cvNamedWindow(name,0); //cvShowImage(name,pI); cvReleaseImage(&pI); } /* */ //printf("Blob %d, point (%.1f,%.1f) size (%.1f,%.1f)\n",m_Blob.ID,m_Blob.x,m_Blob.y,m_Blob.w,m_Blob.h); } /* ::DrawDebug */ private: void Prediction() { int p; for(p=0; p m_ImgSize.width*0.5f) { m_pParticlesPredicted[p].blob.w = m_ImgSize.width*0.5f; } if(m_pParticlesPredicted[p].blob.h > m_ImgSize.height*0.5f) { m_pParticlesPredicted[p].blob.h = m_ImgSize.height*0.5f; } if(m_pParticlesPredicted[p].blob.w < 1 ) { m_pParticlesPredicted[p].blob.w = 1; } if(m_pParticlesPredicted[p].blob.h < 1) { m_pParticlesPredicted[p].blob.h = 1; } } /* "Prediction" of particle. */ } /* Prediction */ void UpdateWeightsMS(IplImage* pImg, IplImage* /*pImgFG*/) { int p; #ifdef _OPENMP if( m_HistForParalel[0].m_pHist==NULL || m_HistForParalel[0].m_pHist->cols != m_BinNumTotal) { int t; for(t=0; t= T)break; } if(p2>=m_ParticleNum)p2=m_ParticleNum-1; m_pParticlesResampled[p] = m_pParticlesPredicted[p2]; m_pParticlesResampled[p].W = 1; } /* Find next particle. */ } /* Resample particle. */ public: virtual void Init(CvBlob* pBlobInit, IplImage* pImg, IplImage* pImgFG = NULL) { int i; CvBlobTrackerOneMSFG::Init(pBlobInit, pImg, pImgFG); DefParticle PP; PP.W = 1; PP.Vx = 0; PP.Vy = 0; PP.blob = pBlobInit[0]; for(i=0;iwidth; m_ImgSize.height = pImg->height; m_Blob = pBlobPrev[0]; { /* Check blob size and realloc kernels if it is necessary: */ int w = cvRound(m_Blob.w); int h = cvRound(m_Blob.h); if( w != m_ObjSize.width || h!=m_ObjSize.height) { ReAllocKernel(w,h); /* After this ( w != m_ObjSize.width || h!=m_ObjSize.height) should be false. */ } } /* Check blob size and realloc kernels if it is necessary. */ Prediction(); #ifdef REPORT_TICKS int64 ticks = cvGetTickCount(); #endif UpdateWeightsMS(pImg, pImgFG); #ifdef REPORT_TICKS ticks = cvGetTickCount() - ticks; fprintf(stderr, "PF UpdateWeights, %d ticks\n", (int)ticks); ticks = cvGetTickCount(); #endif Resample(); #ifdef REPORT_TICKS ticks = cvGetTickCount() - ticks; fprintf(stderr, "PF Resampling, %d ticks\n", (int)ticks); #endif { /* Find average result: */ float x = 0; float y = 0; float w = 0; float h = 0; float Sum = 0; DefParticle* pP = m_pParticlesResampled; for(p=0; p0) { m_Blob.x = x / Sum; m_Blob.y = y / Sum; m_Blob.w = w / Sum; m_Blob.h = h / Sum; } } /* Find average result. */ if(m_Wnd) { DrawDebug(pImg, pImgFG); } return &m_Blob; } /* CvBlobTrackerOneMSPF::Process */ virtual void SkipProcess(CvBlob* pBlob, IplImage* /*pImg*/, IplImage* /*pImgFG*/ = NULL) { int p; for(p=0; p