We propose a solution of the multiple target tracking (MTT) problem based on sets of trajectories and the random finite set framework. A full Bayesian approach to TT should characterize the distribution of the trajectories given the measurements, as it contains all information about the trajectories. We attain this by considering multiobject density functions in which objects are trajectories. For the standard tracking models, we also describe a conjugate family of multitrajectory density functions
In real world multi-target tracking problems, the presence of merged measurements is a frequently oc...
In this paper we propose the set of target trajectories as a state variable for target tracking. We ...
The multiple hypothesis tracker (MHT) and finite set statistics (FISST) are two approaches to multit...
We propose a solution of the multiple target tracking (MTT) problem based on sets of trajectories an...
Over the last few decades multi-target tracking (MTT) has proved to be a challenging and attractive ...
In this paper we present a general solution for multi-target tracking problems with superpositional ...
In multi-target tracking (MTT), the problem of assigning labels to tracks (track labelling) is vastl...
Multi-target tracking requires the joint estimation of the number of target trajectories and their s...
In this article, we propose a metric on the space of finite sets of trajectories for assessing multi...
Multitarget tracking is the process of jointly determining the number of targets present and their s...
In multi-target tracking (MTT), we are often interested not only in finding the position of the mult...
In multi-target tracking (MTT), the problem of assigning labels to tracks (track labelling) is vastl...
Most tracking algorithms in the literature assume that the targets always generate measurements inde...
Multi-target tracking requires the joint estimation of the number of target trajectories and their s...
In this paper we address the problem of tracking multiple targets based on raw measurements by means...
In real world multi-target tracking problems, the presence of merged measurements is a frequently oc...
In this paper we propose the set of target trajectories as a state variable for target tracking. We ...
The multiple hypothesis tracker (MHT) and finite set statistics (FISST) are two approaches to multit...
We propose a solution of the multiple target tracking (MTT) problem based on sets of trajectories an...
Over the last few decades multi-target tracking (MTT) has proved to be a challenging and attractive ...
In this paper we present a general solution for multi-target tracking problems with superpositional ...
In multi-target tracking (MTT), the problem of assigning labels to tracks (track labelling) is vastl...
Multi-target tracking requires the joint estimation of the number of target trajectories and their s...
In this article, we propose a metric on the space of finite sets of trajectories for assessing multi...
Multitarget tracking is the process of jointly determining the number of targets present and their s...
In multi-target tracking (MTT), we are often interested not only in finding the position of the mult...
In multi-target tracking (MTT), the problem of assigning labels to tracks (track labelling) is vastl...
Most tracking algorithms in the literature assume that the targets always generate measurements inde...
Multi-target tracking requires the joint estimation of the number of target trajectories and their s...
In this paper we address the problem of tracking multiple targets based on raw measurements by means...
In real world multi-target tracking problems, the presence of merged measurements is a frequently oc...
In this paper we propose the set of target trajectories as a state variable for target tracking. We ...
The multiple hypothesis tracker (MHT) and finite set statistics (FISST) are two approaches to multit...