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 …

Targets that generate multiple measurements at a given instant in time are commonly known
as extended targets. These present a challenge for many tracking algorithms, as they violate …

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 …

The random hypersurface model (RHM) is introduced for estimating a shape approximation
of an extended object in addition to its kinematic state. An RHM represents the spatial extent …

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 …

This paper presents an extended target tracking method for tracking cars in urban traffic
using data from laser range sensors. Results are presented for three real world datasets that …

This correspondence proposes a new measurement update for extended target tracking
under measurement noise when the target extent is modeled by random matrices …

The main emphases on any object based tracking with vision algorithms are parametric
state space based algorithms like a Bayesian filter and its family of algorithms or …