projects
/
mtp.git
/ commitdiff
commit
grep
author
committer
pickaxe
?
search:
re
summary
|
shortlog
|
log
|
commit
| commitdiff |
tree
raw
|
patch
|
inline
| side by side (parent:
cbe26b6
)
Cosmetics.
author
Francois Fleuret
<francois@fleuret.org>
Tue, 22 Jan 2013 11:30:44 +0000
(12:30 +0100)
committer
Francois Fleuret
<francois@fleuret.org>
Tue, 22 Jan 2013 11:30:44 +0000
(12:30 +0100)
README.txt
patch
|
blob
|
history
diff --git
a/README.txt
b/README.txt
index
c3e14dd
..
095b8a0
100644
(file)
--- a/
README.txt
+++ b/
README.txt
@@
-75,9
+75,9
@@
computation is iterative.
The MTPTracker takes as input
The MTPTracker takes as input
- (1) a
spatial topology composed of
+ (1) a
number of locations and a number of time steps
- - a number of locations
+ (2) a spatial topology composed of
- the allowed motions between them (a Boolean flag for each pair
of locations from/to)
- the allowed motions between them (a Boolean flag for each pair
of locations from/to)
@@
-86,8
+86,6
@@
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)
- (2) a number of time steps
-
(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) )
(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) )
@@
-97,7
+95,7
@@
The MTPTracker takes as input
where the probability that the location is occupied is close to
0, and positive when it is close to 1.
where the probability that the location is occupied is close to
0, and positive when it is close to 1.
-From this parameters,
an
MTPTracker can compute the best set of
+From this parameters,
the
MTPTracker can compute the best set of
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