5 papers
PiVoT: A Variational Solution for Real-time Large-scale Multi-object Detection and Tracking under Heavy Clutter
Runze Gan, Qing Li, Simon J. Godsill +2
Multi-object detection and tracking from noisy point clouds remain challenging in many data-scarce radar applications. Current Bayesian trackers based on Poisson measurement models…
Distributed Expectation Propagation for Multi-Object Tracking over Sensor Networks
Qing Li, Runze Gan, James R. Hopgood +2
In this paper, we present a novel distributed expectation propagation algorithm for multiple sensors, multiple objects tracking in cluttered environments. The proposed framework en…
Decentralised Variational Inference Frameworks for Multi-object Tracking on Sensor Networks: Additional Notes
Qing Li, Runze Gan, Simon Godsill
This paper tackles the challenge of multi-sensor multi-object tracking by proposing various decentralised Variational Inference (VI) schemes that match the tracking performance of…
Consensus-based Distributed Variational Multi-object Tracker in Multi-Sensor Network
Qing Li, Runze Gan, Simon Godsill
The growing need for accurate and reliable tracking systems has driven significant progress in sensor fusion and object tracking techniques. In this paper, we design two variationa…
Variational Tracking and Redetection for Closely-spaced Objects in Heavy Clutter: Supplementary Materials
Runze Gan, Qing Li, Simon Godsill
The non-homogeneous Poisson process (NHPP) is a widely used measurement model that allows for an object to generate multiple measurements over time. However, it can be difficult to…