This work presents the current state-of-the-art in techniques for tracking a number of objects
moving in a coordinated and interacting fashion. Groups are structured objects …

Situation-aware technologies enabled by multitarget tracking will lead to new services and
applications in fields such as autonomous driving, indoor localization, robotic networks, and …

Sequential filtering provides a suitable framework for estimating and updating the unknown
parameters of a system as data become available. The foundations of sequential Bayesian …

We present a simultaneous localization and map** (SLAM) algorithm that is based on
radio signals and the association of specular multipath components (MPCs) with geometric …

We propose an algorithm for tracking an unknown number of targets based on
measurements provided by multiple sensors. Our algorithm achieves low computational …

Mobile robots in real-life settings would benefit from being able to localize and track sound
sources. Such a capability can help localizing a person or an interesting event in the …

Introduction Advanced traffic monitoring systems face significant challenges in vehicle
detection and classification. Conventional methods often require substantial computational …

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 MTT should …

This paper concerns the sequential estimation of a hidden state vector from noisy
observations delivered by several sensors. Different from the standard framework, we …

We address the problem of robust multi-target tracking within the application of hockey
player tracking. The particle filter technique is adopted and modified to fit into the multi-target …