-experiments presented in this article. It uses a Dijkstra with a
-Binary Heap for the min-queue, and not the optimal Fibonacci heap.
+experiments presented in this article. It does not require any
+library, and uses a Dijkstra with a Binary Heap for the min-queue,
+instead of a Fibonacci heap.
- mtp_example creates a tracking toy example, and runs the tracking
algorithm on it. It gives an example of how to use MTPTracker on a
- mtp_example creates a tracking toy example, and runs the tracking
algorithm on it. It gives an example of how to use MTPTracker on a
for the mtp command.
- mtp_stress_test creates a larger problem with a lot of noise and
multiple trajectories, to check the behavior of the code under
for the mtp command.
- mtp_stress_test creates a larger problem with a lot of noise and
multiple trajectories, to check the behavior of the code under
It will load the file tracker.dat saved by the previous command, run
the detection, save the detected trajectories in result.trj, and the
It will load the file tracker.dat saved by the previous command, run
the detection, save the detected trajectories in result.trj, and the
- the entrances (a Boolean flag for each location and time step)
- the exits (a Boolean flag for each location and time step)
- the entrances (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
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
(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) )
where Y is the occupancy of location l at time t and X is the
- available observation. Hence, 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.
+ 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.
disjoint trajectories consistent with the defined topology, which
maximizes the overall detection score (i.e. the sum of the detection
scores of the nodes visited by the trajectories). In particular, if no
disjoint trajectories consistent with the defined topology, which
maximizes the overall detection score (i.e. the sum of the detection
scores of the nodes visited by the trajectories). In particular, if no