International audienceThis article proposes a method to classify multiple maneuvering targets at the same time. This task is a much harder problem than classifying a single target, as sensors do not know how to assign captured measurements to known targets. This article extends previous results scattered in the literature and unifies them in a single global framework with belief functions. Through two examples, it is shown that the full algorithm using belief functions improves results obtained with standard Bayesian classifiers and that it can be applied to a large variety of applications
A sequential Monte Carlo algorithm is suggested for joint maneuvering target tracking and classifica...
In this dissertation, we consider various aspects of tracking multiple targets in clutter. The prima...
[[abstract]]An algorithm of tracking multiple maneuvering targets using a multiple observation syste...
International audienceThis article proposes a method to classify multiple maneuvering targets at the...
International audienceIn this paper, we study the problem of joint tracking and classification of se...
In this paper, we present our findings of investigating non-linear multi-target tracking techniques ...
This letter incorporates the adaptive kernel Kalman filter (AKKF) into the belief propagation (BP) a...
Cette thèse aborde le problèeme du suivi et de la classification de plusieurs objets simultanément.I...
Typical multitarget tracking systems assume that in every scan there is at most one measurement for ...
This paper considers the problem of joint maneuvering target tracking and classification. Based on r...
The original publication can be found at www.springerlink.comThis paper describes a real-time system...
In this paper the Probabilistic Multi-Hypothesis Tracking (PMHT) Algorithm, a data fusion algorithm ...
We introduce an online learning approach for multi-target tracking. Detection responses are graduall...
Abstract—Tracking multiple maneuvering targets in a clut-tered environment is a challenging problem....
A sequential Monte Carlo algorithm is suggested for joint maneuvering target tracking and classific...
A sequential Monte Carlo algorithm is suggested for joint maneuvering target tracking and classifica...
In this dissertation, we consider various aspects of tracking multiple targets in clutter. The prima...
[[abstract]]An algorithm of tracking multiple maneuvering targets using a multiple observation syste...
International audienceThis article proposes a method to classify multiple maneuvering targets at the...
International audienceIn this paper, we study the problem of joint tracking and classification of se...
In this paper, we present our findings of investigating non-linear multi-target tracking techniques ...
This letter incorporates the adaptive kernel Kalman filter (AKKF) into the belief propagation (BP) a...
Cette thèse aborde le problèeme du suivi et de la classification de plusieurs objets simultanément.I...
Typical multitarget tracking systems assume that in every scan there is at most one measurement for ...
This paper considers the problem of joint maneuvering target tracking and classification. Based on r...
The original publication can be found at www.springerlink.comThis paper describes a real-time system...
In this paper the Probabilistic Multi-Hypothesis Tracking (PMHT) Algorithm, a data fusion algorithm ...
We introduce an online learning approach for multi-target tracking. Detection responses are graduall...
Abstract—Tracking multiple maneuvering targets in a clut-tered environment is a challenging problem....
A sequential Monte Carlo algorithm is suggested for joint maneuvering target tracking and classific...
A sequential Monte Carlo algorithm is suggested for joint maneuvering target tracking and classifica...
In this dissertation, we consider various aspects of tracking multiple targets in clutter. The prima...
[[abstract]]An algorithm of tracking multiple maneuvering targets using a multiple observation syste...