Research Project
Researchers: Patrick Peursum (Managed by) , Yasmin Roulston (hasAssociatonWith, isRelatedTo)
Brief description This project focuses on enhancing Multi-Target Tracking (MTT). Multi-Bernoulli Random Finite Set (MB-RFS) filter is a recent model for efficiently performing multi-target tracking in video by representing the state as a multimodal distribution, incorporating data association and target detection into the model itself rather than having them as inputs from external subsystems that can be prone to failure. However, the MB-RFS is based on the non-Bayesian concept of random finite sets and its original derivation does not make it explicit what independence assumptions are being used. This project aims to reformulate the Multi-Bernoulli Random Finite Set MB-RFS as a purely Bayesian model.