4 papers
Multi-Object Posterior Computation via Gibbs Sampling
Ba Tuong Vo, Ba-Ngu Vo
This work presents a tractable approach to multi-object posterior computation under a generic measurement likelihood function. While filtering is a popular solution, valuable histo…
Measurement driven birth model for the generalized labeled multi-Bernoulli filter
S Lin, BT Vo, SE Nordholm
This paper presents a measurement driven birth (MDB) model for the generalized labeled multi-Bernoulli (GLMB) filter. The MDB model adaptively generates target births based on meas…
The Mean of Multi-Object Trajectories
Tran Thien Dat Nguyen, Ba Tuong Vo, Ba-Ngu Vo +2
This paper introduces the concept of a mean for trajectories and multi-object trajectories (defined as sets or multi-sets of trajectories) along with algorithms for computing them.…
Tractable Approximation of Labeled Multi-Object Posterior Densities
Thi Hong Thai Nguyen, Ba-Ngu Vo, Ba-Tuong Vo
Multi-object estimation in state-space models (SSMs) wherein the system state is represented as a finite set has attracted significant interest in recent years. In Bayesian inferen…