31 TrackerStat::TrackerStat(
int binsize) : 
f(100,90) {
    42         if (img == NULL) 
return -1;
    67         if (img == NULL) 
return -1;
    92                         double x = x_curr - x_pred;
    93                         double y = y_curr - y_pred;
    94                         double theta_pred = atan2((
double)y_pred-(
y_res/2), (
double)x_pred-(
x_res/2))*180.0/3.1415926535;
    95                         double theta_curr = atan2((
double)y_curr-(
y_res/2), (
double)x_curr-(
x_res/2))*180.0/3.1415926535;
   106         double xx = *x - (
x_res/2);
   107         double yy = *y - (
y_res/2);
   108         double kosini = cos(
rotd*3.1415926535/180);
   109         double sini = sin(
rotd*3.1415926535/180);
   110         *x = ((kosini * xx) - (sini * yy)) + 
xd + (
x_res/2);
   111         *y = ((sini * xx) + (kosini * yy)) + 
yd + (
y_res/2);
 
CvPoint2D32f * features
Track result: current features 
TrackerStatRot(int binsize=8, int binsize_rot=3)
Constructor. 
double Track(IplImage *img)
Track features. 
int prev_feature_count
Track result: count of previous features 
TFSIMD_FORCE_INLINE const tfScalar & y() const 
void Clear()
Clear the histogram. 
int * prev_ids
Track result: ID:s for previous features 
CvPoint2D32f * prev_features
Track result: previous features 
HistogramSubpixel hist_rot
This file implements a statistical tracker. 
double Track(IplImage *img)
Translation tracker (the simplest possible) 
virtual void Compensate(double *x, double *y)
TFSIMD_FORCE_INLINE const tfScalar & x() const 
int feature_count
Track result: count of current features 
int * ids
Track result: ID:s for current features 
int GetMax(double *dim0, double *dim1=0, double *dim2=0)
Get the maximum from the histogram This finds the maximum bin(s) and averages the original values con...
void AddDimension(int binsize)
Add dimension with a binsize. 
void Inc(double dim0, double dim1=0, double dim2=0)
Increase the histogram for given dimensions. 
double Track(IplImage *img)
Translation + rotation tracker. 
TrackerStat deduces the optical flow based on tracked features using Seppo Valli's statistical tracki...
double rotd
Track result rotation in degrees 
double xd
Track result x-translation in pixels 
double yd
Track result y-translation in pixels 
virtual void Compensate(double *x, double *y)