//============================================================================
void AAM_TDM::DoPCA(const CvMat* AllTextures, double percentage)
{
LOGD("Doing PCA of textures datas...");
int nSamples = AllTextures->rows;
int nPixels = AllTextures->cols;
int nEigenAtMost = MIN(nSamples, nPixels);
CvMat* tmpEigenValues = cvCreateMat(1, nEigenAtMost, CV_64FC1);
CvMat* tmpEigenVectors = cvCreateMat(nEigenAtMost, nPixels, CV_64FC1);
__MeanTexture = cvCreateMat(1, nPixels, CV_64FC1 );
cvCalcPCA(AllTextures, __MeanTexture,
tmpEigenValues, tmpEigenVectors, CV_PCA_DATA_AS_ROW);
double allSum = cvSum(tmpEigenValues).val[0];
double partSum = 0.0;
int nTruncated = 0;
double largesteigval = cvmGet(tmpEigenValues, 0, 0);
for(int i = 0; i < nEigenAtMost; i++)
{
double thiseigval = cvmGet(tmpEigenValues, 0, i);
if(thiseigval / largesteigval < 0.0001) break; // firstly check(remove small values)
partSum += thiseigval;
++ nTruncated;
if(partSum/allSum >= percentage) break; //secondly check
}
__TextureEigenValues = cvCreateMat(1, nTruncated, CV_64FC1);
__TextureEigenVectors = cvCreateMat(nTruncated, nPixels, CV_64FC1);
CvMat G;
cvGetCols(tmpEigenValues, &G, 0, nTruncated);
cvCopy(&G, __TextureEigenValues);
cvGetRows(tmpEigenVectors, &G, 0, nTruncated);
cvCopy(&G, __TextureEigenVectors);
cvReleaseMat(&tmpEigenVectors);
cvReleaseMat(&tmpEigenValues);
LOGD("Done (%d/%d)\n", nTruncated, nEigenAtMost);
}
CvMat* PCA(CvMat *Vector1)
{
int col = Vector1->cols;
CvMat* AvgVector;
CvMat* EigenValue_Row;
CvMat* EigenVector;
AvgVector = cvCreateMat(1, col, CV_32FC1);
EigenValue_Row = cvCreateMat(col, 1, CV_32FC1);
EigenVector = cvCreateMat(col, col, CV_32FC1);
//PrintMatrix(Vector1, RED);
/* cvCalcPCA() */
cvCalcPCA(Vector1,
AvgVector,
EigenValue_Row,
EigenVector,
CV_PCA_DATA_AS_ROW
);
PrintMatrix(AvgVector, BLUE);
/* cvPorjectPCA() */
cvProjectPCA(Vector1,
AvgVector,
EigenVector,
Vector1);
PrintMatrix(Vector1, YELLOW);
PrintMatrix(EigenVector, GREEN);
/* cvBackProjectPCA */
cvBackProjectPCA(Vector1,
AvgVector,
EigenVector,
Vector1);
PrintMatrix(Vector1, BLACK);
cvReleaseMat(&AvgVector);
cvReleaseMat(&EigenVector);
cvReleaseMat(&EigenValue_Row);
return Vector1;
}
void AAM_Train::shape_pca()
{
int dimention=2;
double resudial=0.98;
int ptsNum=shape[0]->ptsNum*dimention;
CvMat *pData=cvCreateMat(shapeNum,ptsNum,CV_64FC1);
for (int i=0;i<shapeNum;i++)
{
for (int j=0;j<ptsNum;j++)
{
//CV_MAT_ELEM(*pData,double,i,j)=shape[i]->ptsForMatlab[j];
//here,we keep the shape in the same scale with the meanshape
CV_MAT_ELEM(*pData,double,i,j)=shape[i]->ptsForMatlab[j];
}
}
s_mean = cvCreateMat(1, ptsNum, CV_64FC1);
s_value = cvCreateMat(1, min(shapeNum,ptsNum), CV_64FC1);
CvMat *s_PCAvec = cvCreateMat( min(shapeNum,ptsNum), ptsNum, CV_64FC1);
cvCalcPCA( pData, s_mean, s_value, s_PCAvec, CV_PCA_DATA_AS_ROW );
double sumEigVal=0;
for (int i=0;i<s_value->cols;i++)
{
sumEigVal+=CV_MAT_ELEM(*s_value,double,0,i);
}
double sumCur=0;
for (int i=0;i<s_value->cols;i++)
{
sumCur+=CV_MAT_ELEM(*s_value,double,0,i);
if (sumCur/sumEigVal>=resudial)
{
shape_dim=i+1;
break;
}
}
//if consider global transform, we will add another 4 shape vector and orthamized?
if (isGlobaltransform)
{
s_vec=cvCreateMat(shape_dim+4,ptsNum,CV_64FC1);
for (int i=0;i<shape_dim;i++)
{
for (int j=0;j<ptsNum;j++)
{
CV_MAT_ELEM(*s_vec,double,i,j)=CV_MAT_ELEM(*s_PCAvec,double,i,j);
}
}
//add the four shape vectors
for (int j=0;j<ptsNum;j++)
{
CV_MAT_ELEM(*s_vec,double,shape_dim+3,j)=meanShape->ptsForMatlab[j];
if (j<ptsNum/2)
{
CV_MAT_ELEM(*s_vec,double,shape_dim+2,j)=-meanShape->ptsForMatlab[ptsNum/2+j];
CV_MAT_ELEM(*s_vec,double,shape_dim+1,j)=1;
CV_MAT_ELEM(*s_vec,double,shape_dim+0,j)=0;
}
else
{
CV_MAT_ELEM(*s_vec,double,shape_dim+2,j)=meanShape->ptsForMatlab[j-ptsNum/2];
CV_MAT_ELEM(*s_vec,double,shape_dim+1,j)=0;
CV_MAT_ELEM(*s_vec,double,shape_dim+0,j)=1;
}
}
