Location estimation is an important part of many ubiquitous computing systems. Particle filters are simulation-based probabilistic approximations which the robotics community has ...
We present in this paper a GPU-accelerated particle filter based on pixel-level segmentation and matching, for real-time object tracking. The proposed method achieves real-time pe...
Particle filters provide a robust framework for nonlinear and non-Gaussian estimation problems. In this paper, we present a method to incorporate dominant modulation-domain (Ampl...
The goal of this article is to present an effective and robust tracking algorithm for nonlinear feet motion by deploying particle filter integrated with Gaussian process latent v...
We propose a distributed implementation of the Gaussian particle filter (GPF) for use in a wireless sensor network. Each sensor runs a local GPF that computes a global state esti...
Ondrej Hlinka, Ondrej Sluciak, Franz Hlawatsch, Pe...