This paper focuses on highly precise localization and tracking of vehicles in race circuits,
where centimeter-level accuracy is required for safety and for enabling complex …

Real-time and accurate vehicle tracking by Cameras and Surveillance can provide strong
support for the acquisition and application of important traffic parameters, which is the basis …

Particle filters (PFs) are a set of Bayesian approaches to estimate the posterior densities of
the state of the systems from given observations using a set of weighted samples. Due to …

Accurate and robust tracking of surrounding road participants plays an important role in
autonomous driving. However, there is usually no prior knowledge of the number of tracking …

In recent years, visual object tracking technologies have been used to track preceding
vehicles in advanced driver assistance systems (ADASs). The accurate positioning of …

The increasing demand for unmanned aerial vehicle (UAV) supervision urgently requires
accurate tracking algorithms as technical support. Particle filter (PF) is widely used for …

While most filtering approaches based on random finite sets have focused on improving
performance, in this paper, we argue that computation times are very important in order to …

Traditional tracking-by-detection systems typically employ Kalman filters (KF) for state
estimation. However, the KF requires domain-specific design choices and it is ill-suited to …

In this work, an improved cubature Kalman filter (CKF), called augmented robust CKF
(ARCKF), for the reentry vehicle trajectory tracking is presented, in which the model strong …

Extended object tracking methods are often based on the assumption that the
measurements are uniformly distributed on the target object. However, this assumption is …