During the last two decades there has been a growing interest in Particle Filtering (PF).
However, PF suffers from two long-standing problems that are referred to as sample …

Agent-based models (ABMs) are gaining traction as one of the most powerful modelling
tools within the social sciences. They are particularly suited to simulating complex systems …

Agent-based modelling is a valuable approach for systems whose behaviour is driven by the
interactions between distinct entities. They have shown particular promise as a means of …

In Extended Target Tracking, where estimating the shape is essential as kinematic,
exploiting the dependencies between targets is often an excellent way to enhance …

Real-time estimation of human mobility following a massive disaster will play a crucial role in
disaster relief. Because human mobility in massive disasters is quite different from their …

Most revolutionary algorithms are inspired from the behavior of natural species. This
inspiration can be drawn from their reproductive behavior, flying mode, or even their ways of …

This paper presents generalized Laplacian eigenmaps, a novel dimensionality reduction
approach designed to address stylistic variations in time series. It generates compact and …

This work addresses the problem of tracking feature points along image sequences. In order
to analyze the undergoing movement, an approach based on the Kalman filtering technique …

This title concerns the use of a particle filter framework to track objects defined in high-
dimensional state-spaces using high-dimensional observation spaces. Current tracking …

This research presents an algorithm for three-dimensional (3-D) pose tracking of a rigid
object by processing sequences of monocular images. The pose trajectory of the object is …