Tracker *tracker = new Tracker(nb_time_steps, nb_locations);
+ // We define the spatial structures by stating what are the possible
+ // motions of targets, and what are the entrances and the
+ // exits.
+
+ // Here our example is a 1D space with motions from any location to
+ // any location less than motion_amplitude away, entrance at
+ // location 0 and exit at location nb_locations-1.
+
for(int l = 0; l < nb_locations; l++) {
for(int k = 0; k < nb_locations; k++) {
tracker->allowed_motion[l][k] = abs(l - k) <= motion_amplitude;
tracker->exits[nb_locations - 1] = 1;
}
+ // We construct the graph corresponding to this structure
+
tracker->build_graph();
- // We generate synthetic detection scores at location
- // nb_locations/2, with 5% false detection (FP or FN)
+ // Then, we specify for every location and time step what is the
+ // detection score there.
scalar_t flip_noise = 0.05;
scalar_t score_noise = 0.0;
+ // We first put a background noise, with negative scores at every
+ // location.
+
for(int t = 0; t < nb_time_steps; t++) {
for(int l = 0; l < nb_locations; l++) {
- tracker->detection_score[t][l] = detection_score(-1.0, 1.0, score_noise, flip_noise);
+ tracker->detection_scores[t][l] = detection_score(-1.0, 1.0, score_noise, flip_noise);
}
}
- // for(int t = 0; t < nb_time_steps; t++) {
- // tracker->detection_score[t][nb_locations/2] = detection_score(1, score_noise, flip_noise);
- // }
-
- // Puts two target with the typical local minimum
-
- int la, lb;
- scalar_t sa, sb;
+ // Then we two targets with the typical local minimum:
+ //
+ // * Target A moves from location 0 to the middle, stays there for a
+ // while, and comes back, and is strongly detected on the first
+ // half
+ //
+ // * Target B moves from location nb_locations-1 to the middle, stay
+ // there for a while, and comes back, and is strongly detected on
+ // the second half
+
+ int la, lb; // Target locations
+ scalar_t sa, sb; // Target detection scores
for(int t = 0; t < nb_time_steps; t++) {
- // Target a moves from location 0 to the middle and comes back,
- // and is strongly detected on the first half, target b moves from
- // location nb_locations-1 to the middle and comes back, and is
- // strongly detected on the second half
if(t < nb_time_steps/2) {
la = t;
lb = nb_locations - 1 - t;
if(la > nb_locations/2 - 1) la = nb_locations/2 - 1;
if(lb < nb_locations/2 + 1) lb = nb_locations/2 + 1;
- tracker->detection_score[t][la] = sa;
- tracker->detection_score[t][lb] = sb;
+ tracker->detection_scores[t][la] = sa;
+ tracker->detection_scores[t][lb] = sb;
}
+ // Does the tracking per se
+
tracker->track();
+ // Prints the detected trajectories
+
for(int t = 0; t < tracker->nb_trajectories(); t++) {
cout << "TRAJECTORY "
<< t
cout << endl;
}
+ // Save the underlying graph in the dot format, with occupied edges
+ // marked in bold.
+
{
ofstream dot("graph.dot");
tracker->print_graph_dot(&dot);
_nb_locations = nb_locations;
_nb_time_steps = nb_time_steps;
- detection_score = allocate_array<scalar_t>(_nb_time_steps, _nb_locations);
+ detection_scores = allocate_array<scalar_t>(_nb_time_steps, _nb_locations);
allowed_motion = allocate_array<int>(_nb_locations, _nb_locations);
entrances = new int[_nb_locations];
for(int t = 0; t < _nb_time_steps; t++) {
for(int l = 0; l < _nb_locations; l++) {
- detection_score[t][l] = 0.0;
+ detection_scores[t][l] = 0.0;
}
}
Tracker::~Tracker() {
delete[] _edge_lengths;
delete _graph;
- deallocate_array<scalar_t>(detection_score);
+ deallocate_array<scalar_t>(detection_scores);
deallocate_array<int>(allowed_motion);
delete[] exits;
delete[] entrances;
int e = 0;
for(int t = 0; t < _nb_time_steps; t++) {
for(int l = 0; l < _nb_locations; l++) {
- _edge_lengths[e++] = - detection_score[t][l];
+ _edge_lengths[e++] = - detection_scores[t][l];
}
}
_graph->print_dot(os);
int e = 0;
for(int t = 0; t < _nb_time_steps; t++) {
for(int l = 0; l < _nb_locations; l++) {
- _edge_lengths[e++] = - detection_score[t][l];
+ _edge_lengths[e++] = - detection_scores[t][l];
}
}