// FexTracker.cpp : Defines the entry point for the DLL application. // #include "StdAfx.h" #include "stdio.h" //#include "mmsystem.h" FexTracker::FexTracker( int sx, int sy, int inFeatures ) { printf( "[ using FexTracker (c)2006 Hajo Krabbenhoft ]\n" ); nFeatures = inFeatures; minFeatures = 0; mFeatures = 8; lFeatures = (FexTrackingFeature*) new FexTrackingFeature[mFeatures]; SizX = sx; SizY = sy; CurImg = 0; CurFrame = 0; bDebug = 0; float subsampling = float(Cfg.SearchRange) / min(Cfg.WindowX,Cfg.WindowY); if (subsampling < 1.0) { /* 1.0 = 0+1 */ PyramidMaxLevels = 1; } else if (subsampling <= 3.0) { /* 3.0 = 2+1 */ PyramidMaxLevels = 2; PyramidSubsampling = 2; } else if (subsampling <= 5.0) { /* 5.0 = 4+1 */ PyramidMaxLevels = 2; PyramidSubsampling = 4; } else if (subsampling <= 9.0) { /* 9.0 = 8+1 */ PyramidMaxLevels = 2; PyramidSubsampling = 8; } else { /* The following lines are derived from the formula: search_range = window_halfwidth * \sum_{i=0}^{nPyramidLevels-1} 8^i, which is the same as: search_range = window_halfwidth * (8^nPyramidLevels - 1)/(8 - 1). Then, the value is rounded up to the nearest integer. */ float val = (float) (log(7.0*subsampling+1.0)/log(8.0)); PyramidMaxLevels = (int) (val + 0.99); PyramidSubsampling = 8; } /* PyramidMaxLevels = 2; PyramidSubsampling = 2; */ } FexTracker::~FexTracker() { delete [] lFeatures; if( CurImg ) delete CurImg; } void FexTracker::ProcessImage( float *Img, bool bFirst ) { //DWORD t = timeGetTime(); if( bFirst || !CurImg ) { CurFrame = 0; CurImg = new FexImgPyramid( Img, SizX, SizY, Cfg.EdgeDetectSigma, Cfg.DetectSmoothSigma, PyramidSubsampling, PyramidMaxLevels ); nActiveFeatures = 0; int tmp = nFeatures; nFeatures = 0; FindFeatures( tmp ); } else { CountActiveFeatures(); if( nActiveFeatures= CurFrame ) nActiveFeatures++; } } FexTrackingFeature* FexTracker::operator [] ( int i ) { if( i<0 || i>=nFeatures ) return 0; return & lFeatures[i]; } int FexTracker::GetEigenvalueForPoint( int px, int py ) { int sx = px - Cfg.WindowX; int ex = px + Cfg.WindowX; int sy = py - Cfg.WindowY; int ey = py + Cfg.WindowY; if( sx<0 )sx=0; if( sy<0 )sy=0; if( ex>SizX-1 )ex=SizX-1; if( ey>SizY-1 )ey=SizY-1; int imgSX = CurImg->lLevels[0]->sx; float* gradx = CurImg->lLevels[0]->GradX; float* grady = CurImg->lLevels[0]->GradY; register float gxx = 0, gyy = 0, gxy = 0; for( int y=sy;y(1<<30) ) val=(1<<30); return (int) val; } typedef struct{ int val, x, y; }littleFeature; #define SWAP3(list, i, j) \ {register int *pi, *pj, tmp; \ pi=list+3*(i); pj=list+3*(j); \ \ tmp=*pi; \ *pi++=*pj; \ *pj++=tmp; \ \ tmp=*pi; \ *pi++=*pj; \ *pj++=tmp; \ \ tmp=*pi; \ *pi=*pj; \ *pj=tmp; \ } void _quicksort(int *pointlist, int n) { unsigned int i, j, ln, rn; while (n > 1) { SWAP3(pointlist, 0, n/2); for (i = 0, j = n; ; ) { do --j; while (pointlist[3*j] < pointlist[0]); do ++i; while (i < j && pointlist[3*i] > pointlist[0]); if (i >= j) break; SWAP3(pointlist, i, j); } SWAP3(pointlist, j, 0); ln = j; rn = n - ++j; if (ln < rn) { _quicksort(pointlist, ln); pointlist += 3*j; n = rn; } else { _quicksort(pointlist + 3*j, rn); n = ln; } } } #undef SWAP3 void FexTracker::FindFeatures( int minFeatures ) { int nli=0; littleFeature *list = new littleFeature[SizX*SizY]; for( int y=0;y0 ) { list[nli].val = v; list[nli].x = x; list[nli].y = y; nli++; } } } _quicksort( (int*)list, nli ); int oldN = nFeatures; for( int i=0;i= mFeatures ) { mFeatures = nFeatures+9; mFeatures -= mFeatures%8; FexTrackingFeature * nlFeatures = (FexTrackingFeature*) new FexTrackingFeature[mFeatures]; for( int cpy=0;cpylLevels[ CurImg->nLevels-1 ]->CoordMul / CurImg->Subsampling; op.y = orig_py * CurImg->lLevels[ CurImg->nLevels-1 ]->CoordMul / CurImg->Subsampling; vec2 np; np = op; for( int l=CurImg->nLevels-1;l>=0;l-- ) { op.x *= CurImg->Subsampling; op.y *= CurImg->Subsampling; np.x *= CurImg->Subsampling; np.y *= CurImg->Subsampling; if( !TrackOneFeature( l, op, np ) ) break; } if( l!=-1 ) continue; //we aborted if( np.x<0 || np.y<0 || np.x>SizX || np.y>SizY ) continue; lFeatures[i].Pos.Add( np ); } } bool FexTracker::TrackOneFeature( int lvl, vec2 op, vec2& np ) { static float bordereps = 1.1f; if( op.x - Cfg.WindowX < bordereps || op.x + Cfg.WindowX > CurImg->lLevels[lvl]->sx - bordereps ) return 0; if( op.y - Cfg.WindowY < bordereps || op.y + Cfg.WindowY > CurImg->lLevels[lvl]->sy - bordereps ) return 0; if( np.x - Cfg.WindowX < bordereps || np.x + Cfg.WindowX > CurImg->lLevels[lvl]->sx - bordereps ) return 0; if( np.y - Cfg.WindowY < bordereps || np.y + Cfg.WindowY > CurImg->lLevels[lvl]->sy - bordereps ) return 0; int isx = (Cfg.WindowX*2+1); int imsiz = isx*(Cfg.WindowY*2+1); float *diff = new float[imsiz]; float *gradx = new float[imsiz]; float *grady = new float[imsiz]; bool bOk = 1; for( int iteration=0;iteration CurImg->lLevels[lvl]->sx - bordereps ) || ( np.y - Cfg.WindowY < bordereps || np.y + Cfg.WindowY > CurImg->lLevels[lvl]->sy - bordereps ) ) { bOk = 0; break; } if( fabs(dx) < Cfg.MinDisplacement && fabs(dy) < Cfg.MinDisplacement )break; } delete [] gradx; delete [] grady; if( bOk ) { GetDiffForPointset( lvl, op, np, diff ); float sum = 0; for( int i=0;i Cfg.MaxResidue ) bOk = 0; } delete [] diff; return bOk; } inline float Interpolate( float *img, int ImgSX, float x, float y ) { int xt = (int) x; /* coordinates of top-left corner */ int yt = (int) y; float ax = x - xt; float ay = y - yt; float *ptr = img + (ImgSX*yt) + xt; return ( (1-ax) * (1-ay) * *ptr + ax * (1-ay) * *(ptr+1) + (1-ax) * ay * *(ptr+(ImgSX)) + ax * ay * *(ptr+(ImgSX)+1) ); } void FexTracker::GetDiffForPointset( int lvl, vec2 op, vec2 np, float* diff ) { float* img1 = CurImg->lLevels[lvl]->Img; int isx1 = CurImg->lLevels[lvl]->sx; float* img2 = NextImg->lLevels[lvl]->Img; int isx2 = NextImg->lLevels[lvl]->sx; for( int y = -Cfg.WindowY; y <= Cfg.WindowY; y++ ) { for( int x = -Cfg.WindowX; x <= Cfg.WindowX; x++ ) { *diff++ = Interpolate(img1,isx1,op.x+x,op.y+y) - Interpolate(img2,isx2,np.x+x,np.y+y); } } } void FexTracker::GetGradForPointset( int lvl, vec2 op, vec2 np, float* gradx, float* grady ) { int isx = CurImg->lLevels[lvl]->sx; float* gx1 = CurImg->lLevels[lvl]->GradX; float* gx2 = NextImg->lLevels[lvl]->GradX; float* gy1 = CurImg->lLevels[lvl]->GradY; float* gy2 = NextImg->lLevels[lvl]->GradY; for( int y = -Cfg.WindowY; y <= Cfg.WindowY; y++ ) { for( int x = -Cfg.WindowX; x <= Cfg.WindowX; x++ ) { *gradx++ = Interpolate(gx1,isx,op.x+x,op.y+y) + Interpolate(gx2,isx,np.x+x,np.y+y); *grady++ = Interpolate(gy1,isx,op.x+x,op.y+y) + Interpolate(gy2,isx,np.x+x,np.y+y); } } } /* static float _minEigenvalue(float gxx, float gxy, float gyy) { return (float) ((gxx + gyy - sqrt((gxx - gyy)*(gxx - gyy) + 4*gxy*gxy))/2.0f); } //gen eigenvalue matrix: gxx = 0; gxy = 0; gyy = 0; for (yy = y-window_hh ; yy <= y+window_hh ; yy++) { for (xx = x-window_hw ; xx <= x+window_hw ; xx++) { gx = *(gradx->data + ncols*yy+xx); gy = *(grady->data + ncols*yy+xx); gxx += gx * gx; gxy += gx * gy; gyy += gy * gy; } } //get eigenvalue number val = _minEigenvalue(gxx, gxy, gyy); for every frame: for every feature: through all pyramid levels from lowres to highres: calculate diff, gradx, grady gen eigenvalue matrix error vector = [gradx, grady]*imdiff float det = gxx*gyy - gxy*gxy; if (det < small) return KLT_SMALL_DET; *dx = (gyy*ex - gxy*ey)/det; *dy = (gxx*ey - gxy*ex)/det; add [dx,dy] to search position */