From: ombz on
Hi all.
I want to track multiple objects on a 2d plane. Now I am having quite some
problems getting the data association (labeling) part working correctly,
i.e. assigning found objects (measurements) to targets. I think I lack some
methodology.
First: objects can appear and disappear at any time, i.e. there is a
variable number of targets and a variable number of measurements at any
time.
Second: there can be a non-significant number of false measurements - this
has nothing to do with a poorly written detection but rather with the
underlying data itself...
I've quickly read about "linear assignment problem" and "joint
probabilistic
data association filter". But if I've correctly understood I cannot use the
linear assignment approach since number of measurements and targets are
both variable and not equal most of the time. Is there some kind of
extension for the linear assignment that I could use in to solve my
problem?
The JPDAF approach seems quite complicated. I think much too complicated
for my problem since the objects to track look all the same, the only thing
that differ are position and color, and maybe the velocity of the objects.
Could you recommend me some simple method to solve the problem? Or some
introductory material to the subject?
Thank you very much