CvGaussBGStatModel2Params params;
CvGaussBGStatModel2Data data;
int countFrames;
-}
-CvGaussBGModel2;
+} CvGaussBGModel2;
CVAPI(CvBGStatModel*) cvCreateGaussianBGModel2( IplImage* first_frame,
CvGaussBGStatModel2Params* params CV_DEFAULT(NULL) );
//shadow detection performed per pixel
// should work for rgb data, could be usefull for gray scale and depth data as well
-// See: Prati,Mikic,Trivedi,Cucchiarra,"Detecting Moving Shadows...",IEEE PAMI,2003.
+// See: Prati,Mikic,Trivedi,Cucchiarra,"Detecting Moving Shadows...",IEEE PAMI,2003.
CV_INLINE int _icvRemoveShadowGMM(float* data, int nD,
- unsigned char nModes,
- CvPBGMMGaussian* pGMM,
- float m_fTb,
- float m_fTB,
- float m_fTau)
+ unsigned char nModes,
+ CvPBGMMGaussian* pGMM,
+ float m_fTb,
+ float m_fTB,
+ float m_fTau)
{
- float tWeight = 0;
- float numerator, denominator;
- // check all the components marked as background:
- for (int iModes=0;iModes<nModes;iModes++)
- {
-
- CvPBGMMGaussian g=pGMM[iModes];
-
- numerator = 0.0f;
- denominator = 0.0f;
- for (int iD=0;iD<nD;iD++)
- {
- numerator += data[iD] * g.mean[iD];
- denominator += g.mean[iD]* g.mean[iD];
- }
-
- // no division by zero allowed
- if (denominator == 0)
- {
- return 0;
- };
- float a = numerator / denominator;
-
- // if tau < a < 1 then also check the color distortion
- if ((a <= 1) && (a >= m_fTau))
- {
-
- float dist2a=0.0f;
-
- for (int iD=0;iD<nD;iD++)
- {
- float dD= a*g.mean[iD] - data[iD];
- dist2a += (dD*dD);
- }
-
- if (dist2a<m_fTb*g.variance*a*a)
- {
- return 2;
- }
- };
-
- tWeight += g.weight;
- if (tWeight > m_fTB)
- {
- return 0;
- };
- };
- return 0;
+ float tWeight = 0;
+ float numerator, denominator;
+ // check all the components marked as background:
+ for (int iModes=0;iModes<nModes;iModes++)
+ {
+
+ CvPBGMMGaussian g=pGMM[iModes];
+
+ numerator = 0.0f;
+ denominator = 0.0f;
+ for (int iD=0;iD<nD;iD++)
+ {
+ numerator += data[iD] * g.mean[iD];
+ denominator += g.mean[iD]* g.mean[iD];
+ }
+
+ // no division by zero allowed
+ if (denominator == 0)
+ {
+ return 0;
+ };
+ float a = numerator / denominator;
+
+ // if tau < a < 1 then also check the color distortion
+ if ((a <= 1) && (a >= m_fTau))
+ {
+
+ float dist2a=0.0f;
+
+ for (int iD=0;iD<nD;iD++)
+ {
+ float dD= a*g.mean[iD] - data[iD];
+ dist2a += (dD*dD);
+ }
+
+ if (dist2a<m_fTb*g.variance*a*a)
+ {
+ return 2;
+ }
+ };
+
+ tWeight += g.weight;
+ if (tWeight > m_fTB)
+ {
+ return 0;
+ };
+ };
+ return 0;
}
//update GMM - the base update function performed per pixel
//http://www.zoranz.net/Publications/zivkovic2004PAMI.pdf
CV_INLINE int _icvUpdateGMM(float* data, int nD,
- unsigned char* pModesUsed,
- CvPBGMMGaussian* pGMM,
- int m_nM,
- float m_fAlphaT,
- float m_fTb,
- float m_fTB,
- float m_fTg,
- float m_fVarInit,
- float m_fVarMax,
- float m_fVarMin,
- float m_fPrune)
+ unsigned char* pModesUsed,
+ CvPBGMMGaussian* pGMM,
+ int m_nM,
+ float m_fAlphaT,
+ float m_fTb,
+ float m_fTB,
+ float m_fTg,
+ float m_fVarInit,
+ float m_fVarMax,
+ float m_fVarMin,
+ float m_fPrune)
{
- //calculate distances to the modes (+ sort)
- //here we need to go in descending order!!!
- bool bBackground=0;//return value -> true - the pixel classified as background
-
- //internal:
- bool bFitsPDF=0;//if it remains zero a new GMM mode will be added
- float m_fOneMinAlpha=1-m_fAlphaT;
- unsigned char nModes=*pModesUsed;//current number of modes in GMM
- float totalWeight=0.0f;
-
- //////
- //go through all modes
- int iMode=0;
- CvPBGMMGaussian* pGauss=pGMM;
- for (;iMode<nModes;iMode++,pGauss++)
- {
- float weight = pGauss->weight;//need only weight if fit is found
- weight=m_fOneMinAlpha*weight+m_fPrune;
-
- ////
- //fit not found yet
- if (!bFitsPDF)
- {
- //check if it belongs to some of the remaining modes
- float var=pGauss->variance;
-
- //calculate difference and distance
- float dist2=0.0f;
+ //calculate distances to the modes (+ sort)
+ //here we need to go in descending order!!!
+ bool bBackground=0;//return value -> true - the pixel classified as background
+
+ //internal:
+ bool bFitsPDF=0;//if it remains zero a new GMM mode will be added
+ float m_fOneMinAlpha=1-m_fAlphaT;
+ unsigned char nModes=*pModesUsed;//current number of modes in GMM
+ float totalWeight=0.0f;
+
+ //////
+ //go through all modes
+ int iMode=0;
+ CvPBGMMGaussian* pGauss=pGMM;
+ for (;iMode<nModes;iMode++,pGauss++)
+ {
+ float weight = pGauss->weight;//need only weight if fit is found
+ weight=m_fOneMinAlpha*weight+m_fPrune;
+
+ ////
+ //fit not found yet
+ if (!bFitsPDF)
+ {
+ //check if it belongs to some of the remaining modes
+ float var=pGauss->variance;
+
+ //calculate difference and distance
+ float dist2=0.0f;
#if (CV_BGFG_MOG2_NDMAX==1)
- float dData=pGauss->mean[0]-data[0];
- dist2=dData*dData;
-#else
- float dData[CV_BGFG_MOG2_NDMAX];
-
- for (int iD=0;iD<nD;iD++)
- {
- dData[iD]=pGauss->mean[iD]-data[iD];
- dist2+=dData[iD]*dData[iD];
- }
-#endif
- //background? - m_fTb - usually larger than m_fTg
- if ((totalWeight<m_fTB)&&(dist2<m_fTb*var))
- bBackground=1;
-
- //check fit
- if (dist2<m_fTg*var)
- {
- /////
- //belongs to the mode - bFitsPDF becomes 1
- bFitsPDF=1;
-
- //update distribution
-
- //update weight
- weight+=m_fAlphaT;
-
- float k = m_fAlphaT/weight;
-
- //update mean
+ float dData=pGauss->mean[0]-data[0];
+ dist2=dData*dData;
+#else
+ float dData[CV_BGFG_MOG2_NDMAX];
+
+ for (int iD=0;iD<nD;iD++)
+ {
+ dData[iD]=pGauss->mean[iD]-data[iD];
+ dist2+=dData[iD]*dData[iD];
+ }
+#endif
+ //background? - m_fTb - usually larger than m_fTg
+ if ((totalWeight<m_fTB)&&(dist2<m_fTb*var))
+ bBackground=1;
+
+ //check fit
+ if (dist2<m_fTg*var)
+ {
+ /////
+ //belongs to the mode - bFitsPDF becomes 1
+ bFitsPDF=1;
+
+ //update distribution
+
+ //update weight
+ weight+=m_fAlphaT;
+
+ float k = m_fAlphaT/weight;
+
+ //update mean
#if (CV_BGFG_MOG2_NDMAX==1)
- pGauss->mean[0]-=k*dData;
-#else
- for (int iD=0;iD<nD;iD++)
- {
- pGauss->mean[iD]-=k*dData[iD];
- }
+ pGauss->mean[0]-=k*dData;
+#else
+ for (int iD=0;iD<nD;iD++)
+ {
+ pGauss->mean[iD]-=k*dData[iD];
+ }
#endif
- //update variance
- float varnew = var + k*(dist2-var);
- //limit the variance
- pGauss->variance = MIN(m_fVarMax,MAX(varnew,m_fVarMin));
-
- //sort
- //all other weights are at the same place and
- //only the matched (iModes) is higher -> just find the new place for it
- for (int iLocal = iMode;iLocal>0;iLocal--)
- {
- //check one up
- if (weight < (pGMM[iLocal-1].weight))
- {
- break;
- }
- else
- {
- //swap one up
- CvPBGMMGaussian temp = pGMM[iLocal];
- pGMM[iLocal] = pGMM[iLocal-1];
- pGMM[iLocal-1] = temp;
- pGauss--;
- }
- }
- //belongs to the mode - bFitsPDF becomes 1
- /////
- }
- }//!bFitsPDF)
-
- //check prune
- if (weight<-m_fPrune)
- {
- weight=0.0;
- nModes--;
- }
-
- pGauss->weight=weight;//update weight by the calculated value
- totalWeight+=weight;
- }
- //go through all modes
- //////
-
- //renormalize weights
- for (iMode = 0; iMode < nModes; iMode++)
- {
- pGMM[iMode].weight = pGMM[iMode].weight/totalWeight;
- }
-
- //make new mode if needed and exit
- if (!bFitsPDF)
- {
- if (nModes==m_nM)
- {
+ //update variance
+ float varnew = var + k*(dist2-var);
+ //limit the variance
+ pGauss->variance = MIN(m_fVarMax,MAX(varnew,m_fVarMin));
+
+ //sort
+ //all other weights are at the same place and
+ //only the matched (iModes) is higher -> just find the new place for it
+ for (int iLocal = iMode;iLocal>0;iLocal--)
+ {
+ //check one up
+ if (weight < (pGMM[iLocal-1].weight))
+ {
+ break;
+ }
+ else
+ {
+ //swap one up
+ CvPBGMMGaussian temp = pGMM[iLocal];
+ pGMM[iLocal] = pGMM[iLocal-1];
+ pGMM[iLocal-1] = temp;
+ pGauss--;
+ }
+ }
+ //belongs to the mode - bFitsPDF becomes 1
+ /////
+ }
+ }//!bFitsPDF)
+
+ //check prune
+ if (weight<-m_fPrune)
+ {
+ weight=0.0;
+ nModes--;
+ }
+
+ pGauss->weight=weight;//update weight by the calculated value
+ totalWeight+=weight;
+ }
+ //go through all modes
+ //////
+
+ //renormalize weights
+ for (iMode = 0; iMode < nModes; iMode++)
+ {
+ pGMM[iMode].weight = pGMM[iMode].weight/totalWeight;
+ }
+
+ //make new mode if needed and exit
+ if (!bFitsPDF)
+ {
+ if (nModes==m_nM)
+ {
//replace the weakest
- pGauss=pGMM+m_nM-1;
- }
- else
- {
+ pGauss=pGMM+m_nM-1;
+ }
+ else
+ {
//add a new one
- pGauss=pGMM+nModes;
- nModes++;
- }
-
- if (nModes==1)
- {
- pGauss->weight=1;
- }
- else
- {
- pGauss->weight=m_fAlphaT;
-
- //renormalize all weights
- for (iMode = 0; iMode < nModes-1; iMode++)
- {
- pGMM[iMode].weight *=m_fOneMinAlpha;
- }
- }
-
- //init
- memcpy(pGauss->mean,data,nD*sizeof(float));
- pGauss->variance=m_fVarInit;
-
- //sort
- //find the new place for it
- for (int iLocal = nModes-1;iLocal>0;iLocal--)
- {
- //check one up
- if (m_fAlphaT < (pGMM[iLocal-1].weight))
- {
- break;
- }
- else
- {
- //swap one up
- CvPBGMMGaussian temp = pGMM[iLocal];
- pGMM[iLocal] = pGMM[iLocal-1];
- pGMM[iLocal-1] = temp;
- }
- }
- }
-
- //set the number of modes
- *pModesUsed=nModes;
+ pGauss=pGMM+nModes;
+ nModes++;
+ }
+
+ if (nModes==1)
+ {
+ pGauss->weight=1;
+ }
+ else
+ {
+ pGauss->weight=m_fAlphaT;
+
+ //renormalize all weights
+ for (iMode = 0; iMode < nModes-1; iMode++)
+ {
+ pGMM[iMode].weight *=m_fOneMinAlpha;
+ }
+ }
+
+ //init
+ memcpy(pGauss->mean,data,nD*sizeof(float));
+ pGauss->variance=m_fVarInit;
+
+ //sort
+ //find the new place for it
+ for (int iLocal = nModes-1;iLocal>0;iLocal--)
+ {
+ //check one up
+ if (m_fAlphaT < (pGMM[iLocal-1].weight))
+ {
+ break;
+ }
+ else
+ {
+ //swap one up
+ CvPBGMMGaussian temp = pGMM[iLocal];
+ pGMM[iLocal] = pGMM[iLocal-1];
+ pGMM[iLocal-1] = temp;
+ }
+ }
+ }
+
+ //set the number of modes
+ *pModesUsed=nModes;
return bBackground;
}
// a bit more efficient implementation for common case of 3 channel (rgb) images
CV_INLINE int _icvUpdateGMM_C3(float r,float g, float b,
- unsigned char* pModesUsed,
- CvPBGMMGaussian* pGMM,
- int m_nM,
- float m_fAlphaT,
- float m_fTb,
- float m_fTB,
- float m_fTg,
- float m_fVarInit,
- float m_fVarMax,
- float m_fVarMin,
- float m_fPrune)
+ unsigned char* pModesUsed,
+ CvPBGMMGaussian* pGMM,
+ int m_nM,
+ float m_fAlphaT,
+ float m_fTb,
+ float m_fTB,
+ float m_fTg,
+ float m_fVarInit,
+ float m_fVarMax,
+ float m_fVarMin,
+ float m_fPrune)
{
- //calculate distances to the modes (+ sort)
- //here we need to go in descending order!!!
- bool bBackground=0;//return value -> true - the pixel classified as background
-
- //internal:
- bool bFitsPDF=0;//if it remains zero a new GMM mode will be added
- float m_fOneMinAlpha=1-m_fAlphaT;
- unsigned char nModes=*pModesUsed;//current number of modes in GMM
- float totalWeight=0.0f;
-
- //////
- //go through all modes
- int iMode=0;
- CvPBGMMGaussian* pGauss=pGMM;
- for (;iMode<nModes;iMode++,pGauss++)
- {
- float weight = pGauss->weight;//need only weight if fit is found
- weight=m_fOneMinAlpha*weight+m_fPrune;
-
- ////
- //fit not found yet
- if (!bFitsPDF)
- {
- //check if it belongs to some of the remaining modes
- float var=pGauss->variance;
-
- //calculate difference and distance
- float muR = pGauss->mean[0];
- float muG = pGauss->mean[1];
- float muB = pGauss->mean[2];
-
- float dR=muR - r;
- float dG=muG - g;
- float dB=muB - b;
-
- float dist2=(dR*dR+dG*dG+dB*dB);
-
- //background? - m_fTb - usually larger than m_fTg
- if ((totalWeight<m_fTB)&&(dist2<m_fTb*var))
- bBackground=1;
-
- //check fit
- if (dist2<m_fTg*var)
- {
- /////
- //belongs to the mode - bFitsPDF becomes 1
- bFitsPDF=1;
-
- //update distribution
-
- //update weight
- weight+=m_fAlphaT;
-
- float k = m_fAlphaT/weight;
-
- //update mean
- pGauss->mean[0] = muR - k*(dR);
- pGauss->mean[1] = muG - k*(dG);
- pGauss->mean[2] = muB - k*(dB);
-
- //update variance
- float varnew = var + k*(dist2-var);
- //limit the variance
- pGauss->variance = MIN(m_fVarMax,MAX(varnew,m_fVarMin));
-
- //sort
- //all other weights are at the same place and
- //only the matched (iModes) is higher -> just find the new place for it
- for (int iLocal = iMode;iLocal>0;iLocal--)
- {
- //check one up
- if (weight < (pGMM[iLocal-1].weight))
- {
- break;
- }
- else
- {
- //swap one up
- CvPBGMMGaussian temp = pGMM[iLocal];
- pGMM[iLocal] = pGMM[iLocal-1];
- pGMM[iLocal-1] = temp;
- pGauss--;
- }
- }
- //belongs to the mode - bFitsPDF becomes 1
- /////
- }
-
- }//!bFitsPDF)
-
- //check prunning
- if (weight<-m_fPrune)
- {
- weight=0.0;
- nModes--;
- }
-
- pGauss->weight=weight;
- totalWeight+=weight;
- }
- //go through all modes
- //////
-
- //renormalize weights
- for (iMode = 0; iMode < nModes; iMode++)
- {
- pGMM[iMode].weight = pGMM[iMode].weight/totalWeight;
- }
-
- //make new mode if needed and exit
- if (!bFitsPDF)
- {
- if (nModes==m_nM)
- {
+ //calculate distances to the modes (+ sort)
+ //here we need to go in descending order!!!
+ bool bBackground=0;//return value -> true - the pixel classified as background
+
+ //internal:
+ bool bFitsPDF=0;//if it remains zero a new GMM mode will be added
+ float m_fOneMinAlpha=1-m_fAlphaT;
+ unsigned char nModes=*pModesUsed;//current number of modes in GMM
+ float totalWeight=0.0f;
+
+ //////
+ //go through all modes
+ int iMode=0;
+ CvPBGMMGaussian* pGauss=pGMM;
+ for (;iMode<nModes;iMode++,pGauss++)
+ {
+ float weight = pGauss->weight;//need only weight if fit is found
+ weight=m_fOneMinAlpha*weight+m_fPrune;
+
+ ////
+ //fit not found yet
+ if (!bFitsPDF)
+ {
+ //check if it belongs to some of the remaining modes
+ float var=pGauss->variance;
+
+ //calculate difference and distance
+ float muR = pGauss->mean[0];
+ float muG = pGauss->mean[1];
+ float muB = pGauss->mean[2];
+
+ float dR=muR - r;
+ float dG=muG - g;
+ float dB=muB - b;
+
+ float dist2=(dR*dR+dG*dG+dB*dB);
+
+ //background? - m_fTb - usually larger than m_fTg
+ if ((totalWeight<m_fTB)&&(dist2<m_fTb*var))
+ bBackground=1;
+
+ //check fit
+ if (dist2<m_fTg*var)
+ {
+ /////
+ //belongs to the mode - bFitsPDF becomes 1
+ bFitsPDF=1;
+
+ //update distribution
+
+ //update weight
+ weight+=m_fAlphaT;
+
+ float k = m_fAlphaT/weight;
+
+ //update mean
+ pGauss->mean[0] = muR - k*(dR);
+ pGauss->mean[1] = muG - k*(dG);
+ pGauss->mean[2] = muB - k*(dB);
+
+ //update variance
+ float varnew = var + k*(dist2-var);
+ //limit the variance
+ pGauss->variance = MIN(m_fVarMax,MAX(varnew,m_fVarMin));
+
+ //sort
+ //all other weights are at the same place and
+ //only the matched (iModes) is higher -> just find the new place for it
+ for (int iLocal = iMode;iLocal>0;iLocal--)
+ {
+ //check one up
+ if (weight < (pGMM[iLocal-1].weight))
+ {
+ break;
+ }
+ else
+ {
+ //swap one up
+ CvPBGMMGaussian temp = pGMM[iLocal];
+ pGMM[iLocal] = pGMM[iLocal-1];
+ pGMM[iLocal-1] = temp;
+ pGauss--;
+ }
+ }
+ //belongs to the mode - bFitsPDF becomes 1
+ /////
+ }
+
+ }//!bFitsPDF)
+
+ //check prunning
+ if (weight<-m_fPrune)
+ {
+ weight=0.0;
+ nModes--;
+ }
+
+ pGauss->weight=weight;
+ totalWeight+=weight;
+ }
+ //go through all modes
+ //////
+
+ //renormalize weights
+ for (iMode = 0; iMode < nModes; iMode++)
+ {
+ pGMM[iMode].weight = pGMM[iMode].weight/totalWeight;
+ }
+
+ //make new mode if needed and exit
+ if (!bFitsPDF)
+ {
+ if (nModes==m_nM)
+ {
//replace the weakest
- pGauss=pGMM+m_nM-1;
- }
- else
- {
+ pGauss=pGMM+m_nM-1;
+ }
+ else
+ {
//add a new one
- pGauss=pGMM+nModes;
- nModes++;
- }
-
- if (nModes==1)
- {
- pGauss->weight=1;
- }
- else
- {
- pGauss->weight=m_fAlphaT;
-
- //renormalize all weights
- for (iMode = 0; iMode < nModes-1; iMode++)
- {
- pGMM[iMode].weight *=m_fOneMinAlpha;
- }
- }
-
- //init
- pGauss->mean[0]=r;
- pGauss->mean[1]=g;
- pGauss->mean[2]=b;
-
- pGauss->variance=m_fVarInit;
-
- //sort
- //find the new place for it
- for (int iLocal = nModes-1;iLocal>0;iLocal--)
- {
- //check one up
- if (m_fAlphaT < (pGMM[iLocal-1].weight))
- {
- break;
- }
- else
- {
- //swap one up
- CvPBGMMGaussian temp = pGMM[iLocal];
- pGMM[iLocal] = pGMM[iLocal-1];
- pGMM[iLocal-1] = temp;
- }
- }
- }
-
- //set the number of modes
- *pModesUsed=nModes;
+ pGauss=pGMM+nModes;
+ nModes++;
+ }
+
+ if (nModes==1)
+ {
+ pGauss->weight=1;
+ }
+ else
+ {
+ pGauss->weight=m_fAlphaT;
+
+ //renormalize all weights
+ for (iMode = 0; iMode < nModes-1; iMode++)
+ {
+ pGMM[iMode].weight *=m_fOneMinAlpha;
+ }
+ }
+
+ //init
+ pGauss->mean[0]=r;
+ pGauss->mean[1]=g;
+ pGauss->mean[2]=b;
+
+ pGauss->variance=m_fVarInit;
+
+ //sort
+ //find the new place for it
+ for (int iLocal = nModes-1;iLocal>0;iLocal--)
+ {
+ //check one up
+ if (m_fAlphaT < (pGMM[iLocal-1].weight))
+ {
+ break;
+ }
+ else
+ {
+ //swap one up
+ CvPBGMMGaussian temp = pGMM[iLocal];
+ pGMM[iLocal] = pGMM[iLocal-1];
+ pGMM[iLocal-1] = temp;
+ }
+ }
+ }
+
+ //set the number of modes
+ *pModesUsed=nModes;
return bBackground;
}
//the main function to update the background model
void icvUpdatePixelBackgroundGMM2( const CvArr* srcarr, CvArr* dstarr ,
- CvPBGMMGaussian *pGMM,
- unsigned char *pUsedModes,
- //CvGaussBGStatModel2Params* pGMMPar,
- int nM,
- float fTb,
- float fTB,
- float fTg,
- float fVarInit,
- float fVarMax,
- float fVarMin,
- float fCT,
- float fTau,
- bool bShadowDetection,
- unsigned char nShadowDetection,
- float alpha)
+ CvPBGMMGaussian *pGMM,
+ unsigned char *pUsedModes,
+ //CvGaussBGStatModel2Params* pGMMPar,
+ int nM,
+ float fTb,
+ float fTB,
+ float fTg,
+ float fVarInit,
+ float fVarMax,
+ float fVarMin,
+ float fCT,
+ float fTau,
+ bool bShadowDetection,
+ unsigned char nShadowDetection,
+ float alpha)
{
- CvMat sstub, *src = cvGetMat(srcarr, &sstub);
+ CvMat sstub, *src = cvGetMat(srcarr, &sstub);
CvMat dstub, *dst = cvGetMat(dstarr, &dstub);
CvSize size = cvGetMatSize(src);
- int nD=CV_MAT_CN(src->type);
+ int nD=CV_MAT_CN(src->type);
- //reshape if possible
+ //reshape if possible
if( CV_IS_MAT_CONT(src->type & dst->type) )
{
size.width *= size.height;
}
int x, y;
- float data[CV_BGFG_MOG2_NDMAX];
- float prune=-alpha*fCT;
-
- //general nD
-
- if (nD!=3)
- {
- switch (CV_MAT_DEPTH(src->type))
- {
- case CV_8U:
- for( y = 0; y < size.height; y++ )
- {
- uchar* sptr = src->data.ptr + src->step*y;
- uchar* pDataOutput = dst->data.ptr + dst->step*y;
- for( x = 0; x < size.width; x++,
- pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
- {
- //convert data
- for (int iD=0;iD<nD;iD++) data[iD]=float(sptr[iD]);
- //update GMM model
- int result = _icvUpdateGMM(data,nD,pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
- //detect shadows in the foreground
- if (bShadowDetection)
- if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
- //generate output
- (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
- }
- }
- break;
- case CV_16S:
- for( y = 0; y < size.height; y++ )
- {
- short* sptr = src->data.s + src->step*y;
- uchar* pDataOutput = dst->data.ptr + dst->step*y;
- for( x = 0; x < size.width; x++,
- pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
- {
- //convert data
- for (int iD=0;iD<nD;iD++) data[iD]=float(sptr[iD]);
- //update GMM model
- int result = _icvUpdateGMM(data,nD,pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
- //detect shadows in the foreground
- if (bShadowDetection)
- if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
- //generate output
- (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
- }
- }
- break;
- case CV_16U:
- for( y = 0; y < size.height; y++ )
- {
- unsigned short* sptr = (unsigned short*) (src->data.s + src->step*y);
- uchar* pDataOutput = dst->data.ptr + dst->step*y;
- for( x = 0; x < size.width; x++,
- pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
- {
- //convert data
- for (int iD=0;iD<nD;iD++) data[iD]=float(sptr[iD]);
- //update GMM model
- int result = _icvUpdateGMM(data,nD,pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
- //detect shadows in the foreground
- if (bShadowDetection)
- if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
- //generate output
- (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
- }
- }
- break;
- case CV_32S:
- for( y = 0; y < size.height; y++ )
- {
- int* sptr = src->data.i + src->step*y;
- uchar* pDataOutput = dst->data.ptr + dst->step*y;
- for( x = 0; x < size.width; x++,
- pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
- {
- //convert data
- for (int iD=0;iD<nD;iD++) data[iD]=float(sptr[iD]);
- //update GMM model
- int result = _icvUpdateGMM(data,nD,pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
- //detect shadows in the foreground
- if (bShadowDetection)
- if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
- //generate output
- (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
- }
- }
- break;
- case CV_32F:
- for( y = 0; y < size.height; y++ )
- {
- float* sptr = src->data.fl + src->step*y;
- uchar* pDataOutput = dst->data.ptr + dst->step*y;
- for( x = 0; x < size.width; x++,
- pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
- {
- //update GMM model
- int result = _icvUpdateGMM(sptr,nD,pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
- //detect shadows in the foreground
- if (bShadowDetection)
- if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
- //generate output
- (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
- }
- }
- break;
- case CV_64F:
- for( y = 0; y < size.height; y++ )
- {
- double* sptr = src->data.db + src->step*y;
- uchar* pDataOutput = dst->data.ptr + dst->step*y;
- for( x = 0; x < size.width; x++,
- pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
- {
- //convert data
- for (int iD=0;iD<nD;iD++) data[iD]=float(sptr[iD]);
- //update GMM model
- int result = _icvUpdateGMM(data,nD,pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
- //detect shadows in the foreground
- if (bShadowDetection)
- if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
- //generate output
- (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
- }
- }
- break;
- }
- }else ///if (nD==3) - a bit faster
- {
- switch (CV_MAT_DEPTH(src->type))
- {
- case CV_8U:
- for( y = 0; y < size.height; y++ )
- {
- uchar* sptr = src->data.ptr + src->step*y;
- uchar* pDataOutput = dst->data.ptr + dst->step*y;
- for( x = 0; x < size.width; x++,
- pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
- {
- //convert data
- data[0]=float(sptr[0]),data[1]=float(sptr[1]),data[2]=float(sptr[2]);
- //update GMM model
- int result = _icvUpdateGMM_C3(data[0],data[1],data[2],pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
- //detect shadows in the foreground
- if (bShadowDetection)
- if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
- //generate output
- (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
- }
- }
- break;
- case CV_16S:
- for( y = 0; y < size.height; y++ )
- {
- short* sptr = src->data.s + src->step*y;
- uchar* pDataOutput = dst->data.ptr + dst->step*y;
- for( x = 0; x < size.width; x++,
- pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
- {
- //convert data
- data[0]=float(sptr[0]),data[1]=float(sptr[1]),data[2]=float(sptr[2]);
- //update GMM model
- int result = _icvUpdateGMM_C3(data[0],data[1],data[2],pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
- //detect shadows in the foreground
- if (bShadowDetection)
- if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
- //generate output
- (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
- }
- }
- break;
- case CV_16U:
- for( y = 0; y < size.height; y++ )
- {
- unsigned short* sptr = (unsigned short*) src->data.s + src->step*y;
- uchar* pDataOutput = dst->data.ptr + dst->step*y;
- for( x = 0; x < size.width; x++,
- pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
- {
- //convert data
- data[0]=float(sptr[0]),data[1]=float(sptr[1]),data[2]=float(sptr[2]);
- //update GMM model
- int result = _icvUpdateGMM_C3(data[0],data[1],data[2],pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
- //detect shadows in the foreground
- if (bShadowDetection)
- if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
- //generate output
- (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
- }
- }
- break;
- case CV_32S:
- for( y = 0; y < size.height; y++ )
- {
- int* sptr = src->data.i + src->step*y;
- uchar* pDataOutput = dst->data.ptr + dst->step*y;
- for( x = 0; x < size.width; x++,
- pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
- {
- //convert data
- data[0]=float(sptr[0]),data[1]=float(sptr[1]),data[2]=float(sptr[2]);
- //update GMM model
- int result = _icvUpdateGMM_C3(data[0],data[1],data[2],pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
- //detect shadows in the foreground
- if (bShadowDetection)
- if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
- //generate output
- (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
- }
- }
- break;
- case CV_32F:
- for( y = 0; y < size.height; y++ )
- {
- float* sptr = src->data.fl + src->step*y;
- uchar* pDataOutput = dst->data.ptr + dst->step*y;
- for( x = 0; x < size.width; x++,
- pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
- {
- //update GMM model
- int result = _icvUpdateGMM_C3(sptr[0],sptr[1],sptr[2],pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
- //detect shadows in the foreground
- if (bShadowDetection)
- if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
- //generate output
- (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
- }
- }
- break;
- case CV_64F:
- for( y = 0; y < size.height; y++ )
- {
- double* sptr = src->data.db + src->step*y;
- uchar* pDataOutput = dst->data.ptr + dst->step*y;
- for( x = 0; x < size.width; x++,
- pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
- {
- //convert data
- data[0]=float(sptr[0]),data[1]=float(sptr[1]),data[2]=float(sptr[2]);
- //update GMM model
- int result = _icvUpdateGMM_C3(data[0],data[1],data[2],pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
- //detect shadows in the foreground
- if (bShadowDetection)
- if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
- //generate output
- (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
- }
- }
- break;
- }
- }//a bit faster for nD=3;
+ float data[CV_BGFG_MOG2_NDMAX];
+ float prune=-alpha*fCT;
+
+ //general nD
+
+ if (nD!=3)
+ {
+ switch (CV_MAT_DEPTH(src->type))
+ {
+ case CV_8U:
+ for( y = 0; y < size.height; y++ )
+ {
+ uchar* sptr = src->data.ptr + src->step*y;
+ uchar* pDataOutput = dst->data.ptr + dst->step*y;
+ for( x = 0; x < size.width; x++,
+ pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
+ {
+ //convert data
+ for (int iD=0;iD<nD;iD++) data[iD]=float(sptr[iD]);
+ //update GMM model
+ int result = _icvUpdateGMM(data,nD,pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
+ //detect shadows in the foreground
+ if (bShadowDetection)
+ if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
+ //generate output
+ (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
+ }
+ }
+ break;
+ case CV_16S:
+ for( y = 0; y < size.height; y++ )
+ {
+ short* sptr = src->data.s + src->step*y;
+ uchar* pDataOutput = dst->data.ptr + dst->step*y;
+ for( x = 0; x < size.width; x++,
+ pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
+ {
+ //convert data
+ for (int iD=0;iD<nD;iD++) data[iD]=float(sptr[iD]);
+ //update GMM model
+ int result = _icvUpdateGMM(data,nD,pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
+ //detect shadows in the foreground
+ if (bShadowDetection)
+ if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
+ //generate output
+ (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
+ }
+ }
+ break;
+ case CV_16U:
+ for( y = 0; y < size.height; y++ )
+ {
+ unsigned short* sptr = (unsigned short*) (src->data.s + src->step*y);
+ uchar* pDataOutput = dst->data.ptr + dst->step*y;
+ for( x = 0; x < size.width; x++,
+ pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
+ {
+ //convert data
+ for (int iD=0;iD<nD;iD++) data[iD]=float(sptr[iD]);
+ //update GMM model
+ int result = _icvUpdateGMM(data,nD,pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
+ //detect shadows in the foreground
+ if (bShadowDetection)
+ if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
+ //generate output
+ (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
+ }
+ }
+ break;
+ case CV_32S:
+ for( y = 0; y < size.height; y++ )
+ {
+ int* sptr = src->data.i + src->step*y;
+ uchar* pDataOutput = dst->data.ptr + dst->step*y;
+ for( x = 0; x < size.width; x++,
+ pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
+ {
+ //convert data
+ for (int iD=0;iD<nD;iD++) data[iD]=float(sptr[iD]);
+ //update GMM model
+ int result = _icvUpdateGMM(data,nD,pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
+ //detect shadows in the foreground
+ if (bShadowDetection)
+ if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
+ //generate output
+ (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
+ }
+ }
+ break;
+ case CV_32F:
+ for( y = 0; y < size.height; y++ )
+ {
+ float* sptr = src->data.fl + src->step*y;
+ uchar* pDataOutput = dst->data.ptr + dst->step*y;
+ for( x = 0; x < size.width; x++,
+ pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
+ {
+ //update GMM model
+ int result = _icvUpdateGMM(sptr,nD,pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
+ //detect shadows in the foreground
+ if (bShadowDetection)
+ if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
+ //generate output
+ (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
+ }
+ }
+ break;
+ case CV_64F:
+ for( y = 0; y < size.height; y++ )
+ {
+ double* sptr = src->data.db + src->step*y;
+ uchar* pDataOutput = dst->data.ptr + dst->step*y;
+ for( x = 0; x < size.width; x++,
+ pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
+ {
+ //convert data
+ for (int iD=0;iD<nD;iD++) data[iD]=float(sptr[iD]);
+ //update GMM model
+ int result = _icvUpdateGMM(data,nD,pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
+ //detect shadows in the foreground
+ if (bShadowDetection)
+ if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
+ //generate output
+ (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
+ }
+ }
+ break;
+ }
+ }else ///if (nD==3) - a bit faster
+ {
+ switch (CV_MAT_DEPTH(src->type))
+ {
+ case CV_8U:
+ for( y = 0; y < size.height; y++ )
+ {
+ uchar* sptr = src->data.ptr + src->step*y;
+ uchar* pDataOutput = dst->data.ptr + dst->step*y;
+ for( x = 0; x < size.width; x++,
+ pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
+ {
+ //convert data
+ data[0]=float(sptr[0]),data[1]=float(sptr[1]),data[2]=float(sptr[2]);
+ //update GMM model
+ int result = _icvUpdateGMM_C3(data[0],data[1],data[2],pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
+ //detect shadows in the foreground
+ if (bShadowDetection)
+ if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
+ //generate output
+ (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
+ }
+ }
+ break;
+ case CV_16S:
+ for( y = 0; y < size.height; y++ )
+ {
+ short* sptr = src->data.s + src->step*y;
+ uchar* pDataOutput = dst->data.ptr + dst->step*y;
+ for( x = 0; x < size.width; x++,
+ pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
+ {
+ //convert data
+ data[0]=float(sptr[0]),data[1]=float(sptr[1]),data[2]=float(sptr[2]);
+ //update GMM model
+ int result = _icvUpdateGMM_C3(data[0],data[1],data[2],pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
+ //detect shadows in the foreground
+ if (bShadowDetection)
+ if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
+ //generate output
+ (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
+ }
+ }
+ break;
+ case CV_16U:
+ for( y = 0; y < size.height; y++ )
+ {
+ unsigned short* sptr = (unsigned short*) src->data.s + src->step*y;
+ uchar* pDataOutput = dst->data.ptr + dst->step*y;
+ for( x = 0; x < size.width; x++,
+ pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
+ {
+ //convert data
+ data[0]=float(sptr[0]),data[1]=float(sptr[1]),data[2]=float(sptr[2]);
+ //update GMM model
+ int result = _icvUpdateGMM_C3(data[0],data[1],data[2],pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
+ //detect shadows in the foreground
+ if (bShadowDetection)
+ if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
+ //generate output
+ (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
+ }
+ }
+ break;
+ case CV_32S:
+ for( y = 0; y < size.height; y++ )
+ {
+ int* sptr = src->data.i + src->step*y;
+ uchar* pDataOutput = dst->data.ptr + dst->step*y;
+ for( x = 0; x < size.width; x++,
+ pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
+ {
+ //convert data
+ data[0]=float(sptr[0]),data[1]=float(sptr[1]),data[2]=float(sptr[2]);
+ //update GMM model
+ int result = _icvUpdateGMM_C3(data[0],data[1],data[2],pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
+ //detect shadows in the foreground
+ if (bShadowDetection)
+ if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
+ //generate output
+ (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
+ }
+ }
+ break;
+ case CV_32F:
+ for( y = 0; y < size.height; y++ )
+ {
+ float* sptr = src->data.fl + src->step*y;
+ uchar* pDataOutput = dst->data.ptr + dst->step*y;
+ for( x = 0; x < size.width; x++,
+ pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
+ {
+ //update GMM model
+ int result = _icvUpdateGMM_C3(sptr[0],sptr[1],sptr[2],pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
+ //detect shadows in the foreground
+ if (bShadowDetection)
+ if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
+ //generate output
+ (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
+ }
+ }
+ break;
+ case CV_64F:
+ for( y = 0; y < size.height; y++ )
+ {
+ double* sptr = src->data.db + src->step*y;
+ uchar* pDataOutput = dst->data.ptr + dst->step*y;
+ for( x = 0; x < size.width; x++,
+ pGMM+=nM,pUsedModes++,pDataOutput++,sptr+=nD)
+ {
+ //convert data
+ data[0]=float(sptr[0]),data[1]=float(sptr[1]),data[2]=float(sptr[2]);
+ //update GMM model
+ int result = _icvUpdateGMM_C3(data[0],data[1],data[2],pUsedModes,pGMM,nM,alpha, fTb, fTB, fTg, fVarInit, fVarMax, fVarMin,prune);
+ //detect shadows in the foreground
+ if (bShadowDetection)
+ if (result==0) result= _icvRemoveShadowGMM(data,nD,(*pUsedModes),pGMM,fTb,fTB,fTau);
+ //generate output
+ (* pDataOutput)= (result==1) ? 0 : (result==2) ? (nShadowDetection) : 255;
+ }
+ }
+ break;
+ }
+ }//a bit faster for nD=3;
}
cvCreateGaussianBGModel2( IplImage* first_frame, CvGaussBGStatModel2Params* parameters )
{
CvGaussBGModel2* bg_model = 0;
- int w,h;
+ int w,h;
CV_FUNCNAME( "cvCreateGaussianBGModel2" );
__BEGIN__;
- CvGaussBGStatModel2Params params;
+ CvGaussBGStatModel2Params params;
if( !CV_IS_IMAGE(first_frame) )
CV_ERROR( CV_StsBadArg, "Invalid or NULL first_frame parameter" );
- if( first_frame->nChannels>CV_BGFG_MOG2_NDMAX )
+ if( first_frame->nChannels>CV_BGFG_MOG2_NDMAX )
CV_ERROR( CV_StsBadArg, "Maxumum number of channels in the image is excedded (change CV_BGFG_MOG2_MAXBANDS constant)!" );
- CV_CALL( bg_model = (CvGaussBGModel2*)cvAlloc( sizeof(*bg_model) ));
+ CV_CALL( bg_model = (CvGaussBGModel2*)cvAlloc( sizeof(*bg_model) ));
memset( bg_model, 0, sizeof(*bg_model) );
bg_model->type = CV_BG_MODEL_MOG2;
bg_model->release = (CvReleaseBGStatModel) icvReleaseGaussianBGModel2;
bg_model->update = (CvUpdateBGStatModel) icvUpdateGaussianBGModel2;
- //init parameters
+ //init parameters
if( parameters == NULL )
- {
- /* These constants are defined in cvaux/include/cvaux.h: */
- params.bShadowDetection = 1;
- params.bPostFiltering=0;
- params.minArea=CV_BGFG_MOG2_MINAREA;
-
- //set parameters
- // K - max number of Gaussians per pixel
- params.nM = CV_BGFG_MOG2_NGAUSSIANS;//4;
- // Tb - the threshold - n var
- //pGMM->fTb = 4*4;
- params.fTb = CV_BGFG_MOG2_STD_THRESHOLD*CV_BGFG_MOG2_STD_THRESHOLD;
- // Tbf - the threshold
- //pGMM->fTB = 0.9f;//1-cf from the paper
- params.fTB = CV_BGFG_MOG2_BACKGROUND_THRESHOLD;
- // Tgenerate - the threshold
- params.fTg = CV_BGFG_MOG2_STD_THRESHOLD_GENERATE*CV_BGFG_MOG2_STD_THRESHOLD_GENERATE;//update the mode or generate new
- //pGMM->fSigma= 11.0f;//sigma for the new mode
- params.fVarInit = CV_BGFG_MOG2_VAR_INIT;
- params.fVarMax = CV_BGFG_MOG2_VAR_MAX;
- params.fVarMin = CV_BGFG_MOG2_VAR_MIN;
- // alpha - the learning factor
- params.fAlphaT = 1.0f/CV_BGFG_MOG2_WINDOW_SIZE;//0.003f;
- // complexity reduction prior constant
- params.fCT = CV_BGFG_MOG2_CT;//0.05f;
-
- //shadow
- // Shadow detection
- params.nShadowDetection = (unsigned char)CV_BGFG_MOG2_SHADOW_VALUE;//value 0 to turn off
- params.fTau = CV_BGFG_MOG2_SHADOW_TAU;//0.5f;// Tau - shadow threshold
+ {
+ memset(¶ms, 0, sizeof(params));
+
+ /* These constants are defined in cvaux/include/cvaux.h: */
+ params.bShadowDetection = 1;
+ params.bPostFiltering=0;
+ params.minArea=CV_BGFG_MOG2_MINAREA;
+
+ //set parameters
+ // K - max number of Gaussians per pixel
+ params.nM = CV_BGFG_MOG2_NGAUSSIANS;//4;
+ // Tb - the threshold - n var
+ //pGMM->fTb = 4*4;
+ params.fTb = CV_BGFG_MOG2_STD_THRESHOLD*CV_BGFG_MOG2_STD_THRESHOLD;
+ // Tbf - the threshold
+ //pGMM->fTB = 0.9f;//1-cf from the paper
+ params.fTB = CV_BGFG_MOG2_BACKGROUND_THRESHOLD;
+ // Tgenerate - the threshold
+ params.fTg = CV_BGFG_MOG2_STD_THRESHOLD_GENERATE*CV_BGFG_MOG2_STD_THRESHOLD_GENERATE;//update the mode or generate new
+ //pGMM->fSigma= 11.0f;//sigma for the new mode
+ params.fVarInit = CV_BGFG_MOG2_VAR_INIT;
+ params.fVarMax = CV_BGFG_MOG2_VAR_MAX;
+ params.fVarMin = CV_BGFG_MOG2_VAR_MIN;
+ // alpha - the learning factor
+ params.fAlphaT = 1.0f/CV_BGFG_MOG2_WINDOW_SIZE;//0.003f;
+ // complexity reduction prior constant
+ params.fCT = CV_BGFG_MOG2_CT;//0.05f;
+
+ //shadow
+ // Shadow detection
+ params.nShadowDetection = (unsigned char)CV_BGFG_MOG2_SHADOW_VALUE;//value 0 to turn off
+ params.fTau = CV_BGFG_MOG2_SHADOW_TAU;//0.5f;// Tau - shadow threshold
}
else
{
params = *parameters;
}
- bg_model->params = params;
+ bg_model->params = params;
- //image data
- w = first_frame->width;
- h = first_frame->height;
+ //image data
+ w = first_frame->width;
+ h = first_frame->height;
- bg_model->params.nWidth = w;
- bg_model->params.nHeight = h;
+ bg_model->params.nWidth = w;
+ bg_model->params.nHeight = h;
- bg_model->params.nND = first_frame->nChannels;
+ bg_model->params.nND = first_frame->nChannels;
- //allocate GMM data
+ //allocate GMM data
- //GMM for each pixel
- bg_model->data.rGMM = (CvPBGMMGaussian*) malloc(w*h * params.nM * sizeof(CvPBGMMGaussian));
- //used modes per pixel
- bg_model->data.rnUsedModes = (unsigned char* ) malloc(w*h);
- memset(bg_model->data.rnUsedModes,0,w*h);//no modes used
+ //GMM for each pixel
+ bg_model->data.rGMM = (CvPBGMMGaussian*) malloc(w*h * params.nM * sizeof(CvPBGMMGaussian));
+ //used modes per pixel
+ bg_model->data.rnUsedModes = (unsigned char* ) malloc(w*h);
+ memset(bg_model->data.rnUsedModes,0,w*h);//no modes used
//prepare storages
CV_CALL( bg_model->background = cvCreateImage(cvSize(w,h), IPL_DEPTH_8U, first_frame->nChannels));
CV_CALL( bg_model->foreground = cvCreateImage(cvSize(w,h), IPL_DEPTH_8U, 1));
- //for eventual filtering
+ //for eventual filtering
CV_CALL( bg_model->storage = cvCreateMemStorage());
-
- bg_model->countFrames = 0;
+
+ bg_model->countFrames = 0;
__END__;
{
CvGaussBGModel2* bg_model = *_bg_model;
- free (bg_model->data.rGMM);
- free (bg_model->data.rnUsedModes);
+ free (bg_model->data.rGMM);
+ free (bg_model->data.rnUsedModes);
cvReleaseImage( &bg_model->background );
cvReleaseImage( &bg_model->foreground );
static int CV_CDECL
icvUpdateGaussianBGModel2( IplImage* curr_frame, CvGaussBGModel2* bg_model )
{
- //checks
- if ((curr_frame->height!=bg_model->params.nHeight)||(curr_frame->width!=bg_model->params.nWidth)||(curr_frame->nChannels!=bg_model->params.nND))
- CV_Error( CV_StsBadSize, "the image not the same size as the reserved GMM background model");
-
- float alpha=bg_model->params.fAlphaT;
- bg_model->countFrames++;
-
- //faster initial updates - increase value of alpha
- if (bg_model->params.bInit){
- float alphaInit=(1.0f/(2*bg_model->countFrames+1));
- if (alphaInit>alpha)
- {
- alpha = alphaInit;
- }
- else
- {
- bg_model->params.bInit = 0;
- }
- }
-
- //update background
- //icvUpdatePixelBackgroundGMM2( curr_frame, bg_model->foreground, bg_model->data.rGMM,bg_model->data.rnUsedModes,&(bg_model->params),alpha);
- icvUpdatePixelBackgroundGMM2( curr_frame, bg_model->foreground, bg_model->data.rGMM,bg_model->data.rnUsedModes,
- bg_model->params.nM,
- bg_model->params.fTb,
- bg_model->params.fTB,
- bg_model->params.fTg,
- bg_model->params.fVarInit,
- bg_model->params.fVarMax,
- bg_model->params.fVarMin,
- bg_model->params.fCT,
- bg_model->params.fTau,
- bg_model->params.bShadowDetection,
- bg_model->params.nShadowDetection,
- alpha);
-
- //foreground filtering
- if (bg_model->params.bPostFiltering==1)
- {
- int region_count = 0;
- CvSeq *first_seq = NULL, *prev_seq = NULL, *seq = NULL;
-
-
- //filter small regions
- cvClearMemStorage(bg_model->storage);
-
- cvMorphologyEx( bg_model->foreground, bg_model->foreground, 0, 0, CV_MOP_OPEN, 1 );
- cvMorphologyEx( bg_model->foreground, bg_model->foreground, 0, 0, CV_MOP_CLOSE, 1 );
-
- cvFindContours( bg_model->foreground, bg_model->storage, &first_seq, sizeof(CvContour), CV_RETR_LIST );
- for( seq = first_seq; seq; seq = seq->h_next )
- {
- CvContour* cnt = (CvContour*)seq;
- if( cnt->rect.width * cnt->rect.height < bg_model->params.minArea )
- {
- //delete small contour
- prev_seq = seq->h_prev;
- if( prev_seq )
- {
- prev_seq->h_next = seq->h_next;
- if( seq->h_next ) seq->h_next->h_prev = prev_seq;
- }
- else
- {
- first_seq = seq->h_next;
- if( seq->h_next ) seq->h_next->h_prev = NULL;
- }
- }
- else
- {
- region_count++;
- }
- }
- bg_model->foreground_regions = first_seq;
- cvZero(bg_model->foreground);
- cvDrawContours(bg_model->foreground, first_seq, CV_RGB(0, 0, 255), CV_RGB(0, 0, 255), 10, -1);
-
- return region_count;
- }
-
- return 1;
+ //checks
+ if ((curr_frame->height!=bg_model->params.nHeight)||(curr_frame->width!=bg_model->params.nWidth)||(curr_frame->nChannels!=bg_model->params.nND))
+ CV_Error( CV_StsBadSize, "the image not the same size as the reserved GMM background model");
+
+ float alpha=bg_model->params.fAlphaT;
+ bg_model->countFrames++;
+
+ //faster initial updates - increase value of alpha
+ if (bg_model->params.bInit){
+ float alphaInit=(1.0f/(2*bg_model->countFrames+1));
+ if (alphaInit>alpha)
+ {
+ alpha = alphaInit;
+ }
+ else
+ {
+ bg_model->params.bInit = 0;
+ }
+ }
+
+ //update background
+ //icvUpdatePixelBackgroundGMM2( curr_frame, bg_model->foreground, bg_model->data.rGMM,bg_model->data.rnUsedModes,&(bg_model->params),alpha);
+ icvUpdatePixelBackgroundGMM2( curr_frame, bg_model->foreground, bg_model->data.rGMM,bg_model->data.rnUsedModes,
+ bg_model->params.nM,
+ bg_model->params.fTb,
+ bg_model->params.fTB,
+ bg_model->params.fTg,
+ bg_model->params.fVarInit,
+ bg_model->params.fVarMax,
+ bg_model->params.fVarMin,
+ bg_model->params.fCT,
+ bg_model->params.fTau,
+ bg_model->params.bShadowDetection,
+ bg_model->params.nShadowDetection,
+ alpha);
+
+ //foreground filtering
+ if (bg_model->params.bPostFiltering==1)
+ {
+ int region_count = 0;
+ CvSeq *first_seq = NULL, *prev_seq = NULL, *seq = NULL;
+
+
+ //filter small regions
+ cvClearMemStorage(bg_model->storage);
+
+ cvMorphologyEx( bg_model->foreground, bg_model->foreground, 0, 0, CV_MOP_OPEN, 1 );
+ cvMorphologyEx( bg_model->foreground, bg_model->foreground, 0, 0, CV_MOP_CLOSE, 1 );
+
+ cvFindContours( bg_model->foreground, bg_model->storage, &first_seq, sizeof(CvContour), CV_RETR_LIST );
+ for( seq = first_seq; seq; seq = seq->h_next )
+ {
+ CvContour* cnt = (CvContour*)seq;
+ if( cnt->rect.width * cnt->rect.height < bg_model->params.minArea )
+ {
+ //delete small contour
+ prev_seq = seq->h_prev;
+ if( prev_seq )
+ {
+ prev_seq->h_next = seq->h_next;
+ if( seq->h_next ) seq->h_next->h_prev = prev_seq;
+ }
+ else
+ {
+ first_seq = seq->h_next;
+ if( seq->h_next ) seq->h_next->h_prev = NULL;
+ }
+ }
+ else
+ {
+ region_count++;
+ }
+ }
+ bg_model->foreground_regions = first_seq;
+ cvZero(bg_model->foreground);
+ cvDrawContours(bg_model->foreground, first_seq, CV_RGB(0, 0, 255), CV_RGB(0, 0, 255), 10, -1);
+
+ return region_count;
+ }
+
+ return 1;
}
nframes = 0;
history = defaultHistory2;
- varThreshold = defaultVarThreshold2;
- bShadowDetection = 1;
-
- nmixtures = defaultNMixtures2;
- backgroundRatio = defaultBackgroundRatio2;
- fVarInit = defaultVarInit2;
- fVarMax = defaultVarMax2;
- fVarMin = defaultVarMin2;
-
- varThresholdGen = defaultVarThresholdGen2;
- fCT = defaultfCT2;
- nShadowDetection = defaultnShadowDetection2;
- fTau = defaultfTau;
+ varThreshold = defaultVarThreshold2;
+ bShadowDetection = 1;
+
+ nmixtures = defaultNMixtures2;
+ backgroundRatio = defaultBackgroundRatio2;
+ fVarInit = defaultVarInit2;
+ fVarMax = defaultVarMax2;
+ fVarMin = defaultVarMin2;
+
+ varThresholdGen = defaultVarThresholdGen2;
+ fCT = defaultfCT2;
+ nShadowDetection = defaultnShadowDetection2;
+ fTau = defaultfTau;
}
BackgroundSubtractorMOG2::BackgroundSubtractorMOG2(int _history, float _varThreshold, bool _bShadowDetection)
nframes = 0;
history = _history > 0 ? _history : defaultHistory2;
- varThreshold = (_varThreshold>0)? _varThreshold : defaultVarThreshold2;
- bShadowDetection = _bShadowDetection;
-
- nmixtures = defaultNMixtures2;
- backgroundRatio = defaultBackgroundRatio2;
- fVarInit = defaultVarInit2;
- fVarMax = defaultVarMax2;
- fVarMin = defaultVarMin2;
-
- varThresholdGen = defaultVarThresholdGen2;
- fCT = defaultfCT2;
- nShadowDetection = defaultnShadowDetection2;
- fTau = defaultfTau;
+ varThreshold = (_varThreshold>0)? _varThreshold : defaultVarThreshold2;
+ bShadowDetection = _bShadowDetection;
+
+ nmixtures = defaultNMixtures2;
+ backgroundRatio = defaultBackgroundRatio2;
+ fVarInit = defaultVarInit2;
+ fVarMax = defaultVarMax2;
+ fVarMin = defaultVarMin2;
+
+ varThresholdGen = defaultVarThresholdGen2;
+ fCT = defaultfCT2;
+ nShadowDetection = defaultnShadowDetection2;
+ fTau = defaultfTau;
}
BackgroundSubtractorMOG2::~BackgroundSubtractorMOG2()
nframes = 0;
int nchannels = CV_MAT_CN(frameType);
- CV_Assert( nchannels <= CV_BGFG_MOG2_NDMAX );
+ CV_Assert( nchannels <= CV_BGFG_MOG2_NDMAX );
// for each gaussian mixture of each pixel bg model we store ...
// the mixture weight (w),
// the mean (nchannels values) and
// the covariance
bgmodel.create( 1, frameSize.height*frameSize.width*nmixtures*(2 + CV_BGFG_MOG2_NDMAX), CV_32F );
- //make the array for keeping track of the used modes per pixel - all zeros at start
- bgmodelUsedModes.create(frameSize,CV_8U);
+ //make the array for keeping track of the used modes per pixel - all zeros at start
+ bgmodelUsedModes.create(frameSize,CV_8U);
bgmodelUsedModes = Scalar::all(0);
}
CV_Assert(learningRate >= 0);
CvMat _cimage = image, _cfgmask = fgmask;
- if (learningRate > 0)
- icvUpdatePixelBackgroundGMM2( &_cimage, &_cfgmask,
- (CvPBGMMGaussian*) bgmodel.data,
- bgmodelUsedModes.data,
- nmixtures,//nM
- varThreshold,//fTb
- backgroundRatio,//fTB
- varThresholdGen,//fTg,
- fVarInit,
- fVarMax,
- fVarMin,
- fCT,
- fTau,
- bShadowDetection,
- nShadowDetection,
- float(learningRate));
+ if (learningRate > 0)
+ icvUpdatePixelBackgroundGMM2( &_cimage, &_cfgmask,
+ (CvPBGMMGaussian*) bgmodel.data,
+ bgmodelUsedModes.data,
+ nmixtures,//nM
+ varThreshold,//fTb
+ backgroundRatio,//fTB
+ varThresholdGen,//fTg,
+ fVarInit,
+ fVarMax,
+ fVarMin,
+ fCT,
+ fTau,
+ bShadowDetection,
+ nShadowDetection,
+ float(learningRate));
}
void BackgroundSubtractorMOG2::getBackgroundImage(OutputArray backgroundImage) const
projects / profile / ivi / opencv.git / commitdiff