X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;ds=sidebyside;f=mtp.cc;h=7f55e0a8a060cafb96d0e961dbeb1ec7dd5e5fc0;hb=4d9b58034ce82094c233b61da247e11a584ec0bd;hp=b80f63b76706c35f6971bfa26f2792270236c071;hpb=5b85b5488da0952f823b2c2cfd3793669fc3ac95;p=mtp.git

diff --git a/mtp.cc b/mtp.cc
index b80f63b..7f55e0a 100644
--- a/mtp.cc
+++ b/mtp.cc
@@ -18,68 +18,121 @@
 
 // Multi-Tracked Path
 
-// Takes the graph description file as input and produces a dot file.
-
-// EXAMPLE: ./mtp ./graph2.txt  | dot -T pdf -o- | xpdf -
-
 #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);
-  graph.print_dot();
+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);
+  }
 }
 
-//////////////////////////////////////////////////////////////////////
-
 int main(int argc, char **argv) {
-  int nb_locations = 6;
-  int nb_time_steps = 10;
+  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.
+
+  // 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->set_allowed_motion(l, k, abs(l - k) <= 1);
+      tracker->allowed_motion[l][k] = abs(l - k) <= motion_amplitude;
     }
+    tracker->entrances[0] = 1;
+    tracker->exits[nb_locations - 1] = 1;
   }
 
-  for(int r = 0; r < 10; r++) {
-    cout << "* ROUND " << r << endl;
-    for(int t = 0; t < nb_time_steps; t++) {
-      for(int l = 0; l < nb_locations; l++) {
-        tracker->set_detection_score(t, l,
-                                    (drand48() < 0.9 ? -1.0 : 1.0) + drand48() * 0.1 - 0.05);
-      }
-      tracker->set_detection_score(t, 0,
-                                  (drand48() < 0.9 ? 1.0 : -1.0) + drand48() * 0.1 - 0.05);
+  // We construct the graph corresponding to this structure
+
+  tracker->build_graph();
+
+  // 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_scores[t][l] = detection_score(-1.0, 1.0, score_noise, flip_noise);
     }
+  }
+
+  // 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);
+    }
+
+    if(la > nb_locations/2 - 1) la = nb_locations/2 - 1;
+    if(lb < nb_locations/2 + 1) lb = nb_locations/2 + 1;
+
+    tracker->detection_scores[t][la] = sa;
+    tracker->detection_scores[t][lb] = sb;
+  }
 
-    tracker->build_graph();
-    tracker->track();
+  // Does the tracking per se
 
-    for(int t = 0; t < tracker->nb_trajectories(); t++) {
-      cout << "TRAJECTORY " << t << " :";
-      for(int u = 0; u < tracker->trajectory_duration(t); u++) {
-        cout << " " << tracker->trajectory_location(t, u);
-      }
-      cout << endl;
+  tracker->track();
+
+  // Prints the detected trajectories
+
+  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;
+  }
+
+  // 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 tracker;