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 …

This paper proposes an efficient implementation of the generalized labeled multi-Bernoulli
(GLMB) filter by combining the prediction and update into a single step. In contrast to an …

This article presents the Labeled Random Finite Set (LRFS) framework for multi-object
systems–systems in which the number of objects and their states are unknown and vary …

Multiobject tracking provides situational awareness that enables new applications for
modern convenience, public safety, and homeland security. This paper presents a factor …

This paper proposes an efficient implementation of the multi-sensor generalized labeled
multi-Bernoulli (GLMB) filter. Like its single-sensor counterpart, such implementation …

This paper presents a Poisson multi-Bernoulli mixture (PMBM) conjugate prior for multiple
extended object filtering. A Poisson point process is used to describe the existence of yet …

Computation and memory resource management strategies are the backbone of continuous
object tracking in intelligent vehicle orchestration. Multi-object tracking generates enormous …

The goal of multi-object tracking is to estimate the number of objects and their states
recursively over time. In the presence of extended objects, ie objects with an extent that is …

Multiple extended target tracking (METT) is a common and challenging problem. Various
solutions for METT have been proposed, however, most of them focus on the single-sensor …