/**********************************************************************
Finds the 150 best features in an image and tracks them through the
next two images. The sequential mode is set in order to speed
processing. The features are stored in a feature table, which is then
saved to a text file; each feature list is also written to a PPM file.
**********************************************************************/
/* this is the example3.c file from the KLT distribution slightly modified */
#include <stdlib.h>
#include <stdio.h>
#include "pnmio.h"
#include "klt.h"
/* #define REPLACE */
void main()
{
unsigned char *img1, *img2;
char fnamein[100], fnameout[100];
KLT_TrackingContext tc;
KLT_FeatureList fl;
KLT_FeatureTable ft;
int nFeatures = 150, nFrames = 100;
int ncols, nrows;
int i, j;
FILE *fp;
tc = KLTCreateTrackingContext();
fl = KLTCreateFeatureList(nFeatures);
ft = KLTCreateFeatureTable(nFrames, nFeatures);
tc->sequentialMode = TRUE;
img1 = pgmReadFile("hotel.seq0.pgm", NULL, &ncols, &nrows);
img2 = (unsigned char *) malloc(ncols*nrows*sizeof(unsigned char));
KLTSelectGoodFeatures(tc, img1, ncols, nrows, fl);
KLTStoreFeatureList(fl, ft, 0);
KLTWriteFeatureListToPPM(fl, img1, ncols, nrows, "feat0.ppm");
for (i = 1 ; i < nFrames ; i++) {
sprintf(fnamein, "hotel.seq%d.pgm", i);
pgmReadFile(fnamein, img2, &ncols, &nrows);
KLTTrackFeatures(tc, img1, img2, ncols, nrows, fl);
#ifdef REPLACE
KLTReplaceLostFeatures(tc, img2, ncols, nrows, fl);
#endif
KLTStoreFeatureList(fl, ft, i);
sprintf(fnameout, "feat%d.ppm", i);
KLTWriteFeatureListToPPM(fl, img2, ncols, nrows, fnameout);
}
fp = fopen("features.dlm", "w");
for (j = 0 ; j < ft->nFeatures ; j++) {
fprintf(fp, "%d, ", j);
for (i = 0 ; i < ft->nFrames - 1; i++)
fprintf(fp, "%.1f, %.1f, %i, ", ft->feature[j][i]->x, ft->feature[j][i]->y, ft->feature[j][i]->val);
fprintf(fp, "%.1f, %.1f, %i\n", ft->feature[j][ft->nFrames - 1]->x, ft->feature[j][ft->nFrames - 1]->y, ft->feature[j][ft->nFrames - 1]->val);
}
KLTWriteFeatureTable(ft, "features.ft", NULL);
}
