void HarrisBuffer::ProcessFrame(IplImage* frm, IplImage* OFx_precomp, IplImage* OFy_precomp)
{
int i;
if (!prevgray) cvCopy(frm,prevgray);
else cvCopy(gray,prevgray);
cvCopy(frm,gray);
cvScale(gray, frame, 1.0/255.0, 0.0);
//Ross moved this 'till later
original.Update(frame);
//spatial filtering
CVUtil::GaussianSmooth(frame, tmp, sig2, FFT);
databuffer.Update(tmp);
//temporal filtering
int tstamp1 = databuffer.TemporalConvolve(tmp1, TemporalMask1);
convbuffer.Update(tmp1, tstamp1);
int tstamp1d = convbuffer.TemporalConvolve(Lt, DerivMask);
cvScale(Lt, Lt, sqrt(tau2_) , 0);
convbuffer.GetFrame(tstamp1d,L);
CVUtil::ImageGradient(L, Lx, Ly); //prb: a possible scale
cvScale(Lx, Lx, sqrt(sig2)*0.5 , 0);
cvScale(Ly, Ly, sqrt(sig2)*0.5 , 0);
//update second-moment matrix
GaussianSmoothingMul(Lx, Lx, tmp1, 2 * sig2);
cxxbuffer.Update(tmp1,tstamp1d);
GaussianSmoothingMul(Lx, Ly, tmp1, 2 * sig2);
cxybuffer.Update(tmp1,tstamp1d);
GaussianSmoothingMul(Lx, Lt, tmp1, 2 * sig2);
cxtbuffer.Update(tmp1,tstamp1d);
GaussianSmoothingMul(Ly, Ly, tmp1, 2 * sig2);
cyybuffer.Update(tmp1,tstamp1d);
GaussianSmoothingMul(Ly, Lt, tmp1, 2 * sig2);
cytbuffer.Update(tmp1,tstamp1d);
GaussianSmoothingMul(Lt, Lt, tmp1, 2 * sig2);
cttbuffer.Update(tmp1, tstamp1d);
//update Harris buffer
int tstamp2=0;
tstamp2=cxxbuffer.TemporalConvolve(cxx, TemporalMask2);
tstamp2=cxybuffer.TemporalConvolve(cxy, TemporalMask2);
tstamp2=cxtbuffer.TemporalConvolve(cxt, TemporalMask2);
tstamp2=cyybuffer.TemporalConvolve(cyy, TemporalMask2);
tstamp2=cytbuffer.TemporalConvolve(cyt, TemporalMask2);
tstamp2=cttbuffer.TemporalConvolve(ctt, TemporalMask2);
// Estimate L&K optical flow from second moment matrix
//OpticalFlowFromSMM();
//OpticalFlowFromLK();
OFx=OFx_precomp;
OFy=OFy_precomp;
// compute 3D extension of Harris function
HarrisFunction(kparam, tmp);
Hbuffer.Update(tmp,tstamp2);
//*** detect interest points
DetectInterestPoints(Border);
//*** compute point descriptors
for(i=0;i<(int)ipList.size();i++) {
if(!ipList[i].reject)
{
DetectedTrackingPoint dtp(ipList[i]);
//Here I want to add the interest point to the list of interest-points-to-track
pointsToTrack.push_back(dtp);
}
}
//here's where I do the tracking
// go through pointsToTrack
// for everything that hasn't finished tracking
// add it's most recent location to the list that the openCV KLT function will take
// run the opencv KLT function
// using the same "for" structure that added the points to the tracking list,
// go through those points, and either add the new tracked position to the point
// or, if tracking was lost,
// remove the point from pointsToTrack, and add it to pointsFinishedTracking
//first, allocate the prev_features structure
CalculateVelocityHistories();
iFrame++;
return;
}
void HarrisBuffer::ProcessFrame(IplImage* frm)
{
gray=frm;
//todo:scale depending on input type and IMGTYPE
//cvNormalize(gray,frame,1,0,CV_MINMAX);
/*double m, M;
cvMinMaxLoc(gray, &m, &M, NULL, NULL, NULL);*/
cvScale(gray, frame, 1.0/255.0, 0.0);//
/*double m, M;
cvMinMaxLoc(frame, &m, &M, NULL, NULL, NULL);
std::cout<<m<<"\t"<<M<<endl;*/
original.Update(frame);
//spatial filtering
CVUtil::GaussianSmooth(frame,tmp,sig2,FFT);
databuffer.Update(tmp);
//temporal filtering
int tstamp1=databuffer.TemporalConvolve(tmp1, TemporalMask1);
convbuffer.Update(tmp1,tstamp1);
int tstamp1d=convbuffer.TemporalConvolve(Lt,DerivMask);
cvScale(Lt,Lt, sqrt(tau2) , 0);
convbuffer.GetFrame(tstamp1d,L);
CVUtil::ImageGradient(L,Lx,Ly);//prb: a possible scale
cvScale(Lx,Lx, sqrt(sig2)*0.5 , 0);
cvScale(Ly,Ly, sqrt(sig2)*0.5 , 0);
//update second-moment matrix
GaussianSmoothingMul(Lx,Lx, tmp1,2*sig2);
cxxbuffer.Update(tmp1,tstamp1d);
GaussianSmoothingMul(Lx,Ly, tmp1,2*sig2);
cxybuffer.Update(tmp1,tstamp1d);
GaussianSmoothingMul(Lx,Lt, tmp1,2*sig2);
cxtbuffer.Update(tmp1,tstamp1d);
GaussianSmoothingMul(Ly,Ly, tmp1,2*sig2);
cyybuffer.Update(tmp1,tstamp1d);
GaussianSmoothingMul(Ly,Lt, tmp1,2*sig2);
cytbuffer.Update(tmp1,tstamp1d);
GaussianSmoothingMul(Lt,Lt, tmp1,2*sig2);
cttbuffer.Update(tmp1,tstamp1d);
//update Harris buffer
int tstamp2=0;
tstamp2=cxxbuffer.TemporalConvolve(cxx, TemporalMask2);
tstamp2=cxybuffer.TemporalConvolve(cxy, TemporalMask2);
tstamp2=cxtbuffer.TemporalConvolve(cxt, TemporalMask2);
tstamp2=cyybuffer.TemporalConvolve(cyy, TemporalMask2);
tstamp2=cytbuffer.TemporalConvolve(cyt, TemporalMask2);
tstamp2=cttbuffer.TemporalConvolve(ctt, TemporalMask2);
HarrisFunction(kparam, tmp);
Hbuffer.Update(tmp,tstamp2);
//LogMinMax(Hbuffer.Buffer,logfile);
//databuffer.FrameIndices.print(std::cout);
//databuffer.FrameIndices.print(logfile);
//convbuffer.FrameIndices.print(logfile);
//Hbuffer.FrameIndices.print(logfile);
//std::cout<<iFrame<<std::endl;
DetectInterestPoints(Border);
iFrame++;
return;
}
