void ComputeMeanAndVariance(Array2d<double>& data,Array2dC<double>& avg,Array2d<double>& cov,const bool subtractMean)
{
avg.Create(1,data.ncol); avg.Zero();
cov.Create(data.ncol,data.ncol); cov.Zero();
for(int i=0;i<data.nrow;i++)
{
for(int j=0;j<data.ncol;j++) avg.buf[j] += data.p[i][j];
for(int j=0;j<data.ncol;j++)
for(int k=0;k<data.ncol;k++)
cov.p[j][k] += data.p[i][j]*data.p[i][k];
}
const double r = 1.0/data.nrow;
for(int i=0;i<data.ncol;i++) avg.buf[i] *= r;
if(subtractMean)
{
for(int i=0;i<data.ncol;i++)
for(int j=0;j<data.ncol;j++)
cov.p[i][j] = cov.p[i][j]*r-avg.buf[i]*avg.buf[j];
}
else
{
for(int i=0;i<data.ncol;i++)
for(int j=0;j<data.ncol;j++)
cov.p[i][j] = cov.p[i][j]*r;
}
}
// The function that does the real detection
int DetectionScanner::FastScan(IntImage<double>& original,std::vector<CRect>& results,const int stepsize)
{
if(original.nrow<height+5 || original.ncol<width+5) return 0;
const int hd = height/xdiv;
const int wd = width/ydiv;
InitImage(original);
results.clear();
hist.Create(1,baseflength*(xdiv-EXT)*(ydiv-EXT));
NodeDetector* node = cascade->nodes[1];
double** pc = node->classifier.p;
int oheight = original.nrow, owidth = original.ncol;
CRect rect;
while(image.nrow>=height && image.ncol>=width)
{
InitIntegralImages(stepsize);
for(int i=2; i+height<image.nrow-2; i+=stepsize)
{
const double* sp = scores.p[i];
for(int j=2; j+width<image.ncol-2; j+=stepsize)
{
if(sp[j]<=0) continue;
int* p = hist.buf;
hist.Zero();
for(int k=0; k<xdiv-EXT; k++)
{
for(int t=0; t<ydiv-EXT; t++)
{
for(int x=i+k*hd+1; x<i+(k+1+EXT)*hd-1; x++)
{
int* ctp = ct.p[x];
for(int y=j+t*wd+1; y<j+(t+1+EXT)*wd-1; y++)
p[ctp[y]]++;
}
p += baseflength;
}
}
double score = node->thresh;
for(int k=0; k<node->classifier.nrow; k++) score += pc[k][hist.buf[k]];
if(score>0)
{
rect.top = i*oheight/image.nrow;
rect.bottom = (i+height)*oheight/image.nrow;
rect.left = j*owidth/image.ncol;
rect.right = (j+width)*owidth/image.ncol;
results.push_back(rect);
}
}
}
ResizeImage();
}
return 0;
}