+++ /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. */
- }
-
- ~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