772 citations · 2.1k across the 28 of their papers we have counts for
32 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…
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…
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.…
An Overview of Multi-Object Estimation via Labeled Random Finite Set
Ba-Ngu Vo, Ba-Tuong Vo, Tran Thien Dat Nguyen +1
This article presents the Labeled Random Finite Set (LRFS) framework for multi-object systems-systems in which the number of objects and their states are unknown and vary randomly…
Linear Complexity Gibbs Sampling for Generalized Labeled Multi-Bernoulli Filtering
Changbeom Shim, Ba-Tuong Vo, Ba-Ngu Vo +2
Generalized Labeled Multi-Bernoulli (GLMB) densities arise in a host of multi-object system applications analogous to Gaussians in single-object filtering. However, computing the G…
Multi-Scan Multi-Sensor Multi-Object State Estimation
D. Moratuwage, B. -N. Vo, B. -T. Vo +1
If computational tractability were not an issue, multi-object estimation should integrate all measurements from multiple sensors across multiple scans. In this article, we propose…