// Multi-Tracked Path
-// Takes the graph description file as input and produces a dot file.
-
-// EXAMPLE: ./mtp ./graph2.txt | dot -T pdf -o- | xpdf -
-
-#define VERBOSE
-
#include <iostream>
#include <fstream>
-#include <cmath>
-#include <stdio.h>
-#include <stdlib.h>
-#include <float.h>
using namespace std;
-#include "mtp_graph.h"
+#include "tracker.h"
//////////////////////////////////////////////////////////////////////
-void find_best_paths(int nb_vertices,
- int nb_edges, int *ea, int *eb, scalar_t *el,
- int source, int sink,
- int *result_edge_occupation) {
- MTPGraph graph(nb_vertices, nb_edges, ea, eb, source, sink);
- graph.find_best_paths(el, result_edge_occupation);
-}
-
-void dot_print(int nb_vertices,
- int nb_edges, int *ea, int *eb, scalar_t *el,
- int source, int sink,
- int *edge_occupation) {
- cout << "digraph {" << endl;
- cout << " node[shape=circle];" << endl;
- for(int e = 0; e < nb_edges; e++) {
- if(edge_occupation[e]) {
- cout << " " << ea[e] << " -> " << eb[e] << " [style=bold,color=black,label=\"" << el[e] << "\"];" << endl;
- } else {
- cout << " " << ea[e] << " -> " << eb[e] << " [color=gray,label=\"" << el[e] << "\"];" << endl;
- }
+scalar_t detection_score(scalar_t a, scalar_t b, scalar_t score_noise, scalar_t flip_noise) {
+ if(drand48() > flip_noise) {
+ return a + score_noise * (2.0 * drand48() - 1.0);
+ } else {
+ return b + score_noise * (2.0 * drand48() - 1.0);
}
- cout << "}" << endl;
}
-//////////////////////////////////////////////////////////////////////
-
int main(int argc, char **argv) {
+ int nb_locations = 7;
+ int nb_time_steps = 8;
+ int motion_amplitude = 1;
+
+ 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.
- if(argc < 2) {
- cerr << argv[0] << " <graph file>" << endl;
- exit(EXIT_FAILURE);
+ // 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->entrances[0] = 1;
+ tracker->exits[nb_locations - 1] = 1;
}
- ifstream *file = new ifstream(argv[1]);
+ // We construct the graph corresponding to this structure
+
+ tracker->build_graph();
- int nb_edges, nb_vertices;
- int source, sink;
+ // Then, we specify for every location and time step what is the
+ // detection score there.
- if(file->good()) {
+ scalar_t flip_noise = 0.05;
+ scalar_t score_noise = 0.0;
- (*file) >> nb_vertices >> nb_edges;
- (*file) >> source >> sink;
+ // We first put a background noise, with negative scores at every
+ // location.
- scalar_t *edge_lengths = new scalar_t[nb_edges];
- int *vertex_from = new int[nb_edges];
- int *vertex_to = new int[nb_edges];
- int *result_edge_occupation = new int[nb_edges];
+ for(int t = 0; t < nb_time_steps; t++) {
+ for(int l = 0; l < nb_locations; l++) {
+ tracker->detection_scores[t][l] = detection_score(-1.0, 1.0, score_noise, flip_noise);
+ }
+ }
- for(int e = 0; e < nb_edges; e++) {
- (*file) >> vertex_from[e] >> vertex_to[e] >> edge_lengths[e];
+ // 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++) {
+ if(t < nb_time_steps/2) {
+ la = t;
+ lb = nb_locations - 1 - t;
+ sa = detection_score(10.0, -1.0, score_noise, flip_noise);
+ sb = detection_score( 1.0, -1.0, score_noise, flip_noise);
+ } else {
+ la = nb_time_steps - 1 - t;
+ lb = t - nb_time_steps + nb_locations;
+ sa = detection_score( 1.0, -1.0, score_noise, flip_noise);
+ sb = detection_score(10.0, -1.0, score_noise, flip_noise);
}
- find_best_paths(nb_vertices, nb_edges,
- vertex_from, vertex_to, edge_lengths,
- source, sink,
- result_edge_occupation);
+ if(la > nb_locations/2 - 1) la = nb_locations/2 - 1;
+ if(lb < nb_locations/2 + 1) lb = nb_locations/2 + 1;
- dot_print(nb_vertices, nb_edges,
- vertex_from, vertex_to, edge_lengths,
- source, sink,
- result_edge_occupation);
+ tracker->detection_scores[t][la] = sa;
+ tracker->detection_scores[t][lb] = sb;
+ }
- delete[] result_edge_occupation;
- delete[] edge_lengths;
- delete[] vertex_from;
- delete[] vertex_to;
+ // Does the tracking per se
- } else {
+ tracker->track();
+
+ // Prints the detected trajectories
- cerr << "Can not open " << argv[1] << endl;
+ for(int t = 0; t < tracker->nb_trajectories(); t++) {
+ cout << "TRAJECTORY "
+ << t
+ << " [starting " << tracker->trajectory_entrance_time(t)
+ << ", score " << tracker->trajectory_score(t) << "]";
+ for(int u = 0; u < tracker->trajectory_duration(t); u++) {
+ cout << " " << tracker->trajectory_location(t, u);
+ }
+ cout << endl;
+ }
- delete file;
- exit(EXIT_FAILURE);
+ // Save the underlying graph in the dot format, with occupied edges
+ // marked in bold.
+ {
+ ofstream dot("graph.dot");
+ tracker->print_graph_dot(&dot);
+ cout << "Wrote graph.dot." << endl;
}
- delete file;
+ delete tracker;
+
exit(EXIT_SUCCESS);
}