This tutorial introduces state-of-the-art methods for tracking multiple spatially extended
objects based on unlabeled noisy point clouds, eg, from radar or lidar sensors. In the first …

This article provides an elaborate overview of current research in extended object tracking.
We provide a clear definition of the extended object tracking problem and discuss its …

In this paper, we propose using Gaussian processes to track an extended object or group of
objects, that generates multiple measurements at each scan. The shape and the kinematics …

This paper presents a random set based approach to tracking of an unknown number of
extended targets, in the presence of clutter measurements and missed detections, where the …

This paper presents a Gaussian-mixture (GM) implementation of the probability hypothesis
density (PHD) filter for tracking extended targets. The exact filter requires processing of all …

<? Pub Dtl=""?> This paper presents a cardinalized probability hypothesis density (CPHD)
filter for extended targets that can result in multiple measurements at each scan. The …

In this study, we propose a novel extended target tracking algorithm which is capable of
representing the extent of dynamic objects as an ellipsoid with a time-varying orientation …

X-band marine radar systems represent a flexible and low-cost tool for the tracking of
multiple targets in a given region of interest. Although suffering several sources of …

Extended object tracking considers the simultaneous estimation of the kinematic state and
the shape parameters of a moving object based on a varying number of noisy detections …

The objective of extended object tracking is to simultaneously track a target object and
estimate its shape. As a consequence, it becomes necessary to incorporate both location …