Added README.md

diff --git a/README.txt b/README.md
similarity index 85%
rename from README.txt
rename to README.md
index 18266af..b1ac38d 100644 (file)
--- a/README.txt
+++ b/README.md
@@ -1,17 +1,13 @@
-
-                       Multi-Tracked Paths (MTP)
-                       -------------------------
-
-* INTRODUCTION
+# Introduction

 
 This is a very simple implementation of a variant of the k-shortest
 paths algorithm (KSP) applied to multi-target tracking, as described
 in
 
 
 This is a very simple implementation of a variant of the k-shortest
 paths algorithm (KSP) applied to multi-target tracking, as described
 in
 

-  J. Berclaz, E. Turetken, F. Fleuret, and P. Fua. Multiple Object
-  Tracking using K-Shortest Paths Optimization. IEEE Transactions on
-  Pattern Analysis and Machine Intelligence (TPAMI), 33(9):1806-1819,
-  2011.
+ > J. Berclaz, E. Turetken, F. Fleuret, and P. Fua. Multiple Object
+ > Tracking using K-Shortest Paths Optimization. IEEE Transactions on
+ > Pattern Analysis and Machine Intelligence (TPAMI),
+ > 33(9):1806--1819, 2011.

 
 This implementation is not the reference implementation used for the
 experiments presented in this article. It does not require any
 
 This implementation is not the reference implementation used for the
 experiments presented in this article. It does not require any


@@ -31,13 +27,15 @@ This software package provides two commands:
    for the mtp command. If you pass it the "stress" argument, it
    generates a larger and noisier problem.
 
    for the mtp command. If you pass it the "stress" argument, it
    generates a larger and noisier problem.
 

-* INSTALLATION
+# Installation

 
 This software should compile with any C++ compiler. Under a unix-like
 environment, just execute
 
 
 This software should compile with any C++ compiler. Under a unix-like
 environment, just execute
 

-  make
-  ./mtp_example
+```
+make
+./mtp_example
+```

 
 It will create a synthetic dummy example, save its description in
 tracker.dat, and print the optimal detected trajectories.
 
 It will create a synthetic dummy example, save its description in
 tracker.dat, and print the optimal detected trajectories.


@@ -55,7 +53,7 @@ pdf from the latter with the dot command:
 
   dot < graph.dot -T pdf -o graph.pdf
 
 
   dot < graph.dot -T pdf -o graph.pdf
 

-* IMPLEMENTATION
+# Implementation

 
 The two main classes are MTPGraph and MTPTracker.
 
 
 The two main classes are MTPGraph and MTPTracker.
 


@@ -72,9 +70,9 @@ computation is iterative.
 
 The MTPTracker takes as input
 
 
 The MTPTracker takes as input
 

- (1) a number of locations and a number of time steps
+1. a number of locations and a number of time steps

 
 

- (2) a spatial topology composed of
+2. a spatial topology composed of

 
      - the allowed motions between locations (a Boolean flag for each
        pair of locations from/to)
 
      - the allowed motions between locations (a Boolean flag for each
        pair of locations from/to)


@@ -83,14 +81,14 @@ The MTPTracker takes as input
 
      - the exits (a Boolean flag for each location and time step)
 
 
      - the exits (a Boolean flag for each location and time step)
 

- (3) a detection score for every location and time, which stands for
+3. a detection score for every location and time, which stands for

 
              log( P(Y(l,t) = 1 | X) / P(Y(l,t) = 0 | X) )
 
 
              log( P(Y(l,t) = 1 | X) / P(Y(l,t) = 0 | X) )
 

-     where Y is the occupancy of location l at time t and X is the
-     available observation. In particular, this score is negative on
-     locations where the probability that the location is occupied is
-     close to 0, and positive when it is close to 1.
+   where Y is the occupancy of location l at time t and X is the
+   available observation. In particular, this score is negative on
+   locations where the probability that the location is occupied is
+   close to 0, and positive when it is close to 1.

 
 From this parameters, the MTPTracker can compute the best set of
 disjoint trajectories consistent with the defined topology, which
 
 From this parameters, the MTPTracker can compute the best set of
 disjoint trajectories consistent with the defined topology, which


@@ -116,6 +114,7 @@ running the tracking.
 The tracker data file for MTPTracker::read has the following format,
 where L is the number of locations and T is the number of time steps:
 
 The tracker data file for MTPTracker::read has the following format,
 where L is the number of locations and T is the number of time steps:
 

+```

 ---------------------------- snip snip -------------------------------
   int:L int:T
 
 ---------------------------- snip snip -------------------------------
   int:L int:T
 


@@ -135,15 +134,14 @@ where L is the number of locations and T is the number of time steps:
   ...
   float:detection_score_T_1 ... float:detection_score_T_L
 ---------------------------- snip snip -------------------------------
   ...
   float:detection_score_T_1 ... float:detection_score_T_L
 ---------------------------- snip snip -------------------------------

+```

 
 The method MTPTracker::write_trajectories writes first the number of
 trajectories, followed by one line per trajectory with the following
 structure
 
 
 The method MTPTracker::write_trajectories writes first the number of
 trajectories, followed by one line per trajectory with the following
 structure
 

+```

 ---------------------------- snip snip -------------------------------
   int:traj_number int:entrance_time int:duration float:score int:location_1 ... int:location_duration
 ---------------------------- snip snip -------------------------------
 ---------------------------- snip snip -------------------------------
   int:traj_number int:entrance_time int:duration float:score int:location_1 ... int:location_duration
 ---------------------------- snip snip -------------------------------

-
---
-François Fleuret
-April 2013
+```