4 citations · 12 across the 9 of their papers we have counts for
5 papers · 1 filter
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…
A Multi-Scan Labeled Random Finite Set Model for Multi-object State Estimation
Ba Tuong Vo, Ba Ngu Vo
State space models in which the system state is a finite set--called the multi-object state--have generated considerable interest in recent years. Smoothing for state space models…
A Solution for Large-scale Multi-object Tracking
Michael Beard, Ba Tuong Vo, Ba-Ngu Vo
A large-scale multi-object tracker based on the generalised labeled multi-Bernoulli (GLMB) filter is proposed. The algorithm is capable of tracking a very large, unknown and time-v…
Multi-Sensor Multi-object Tracking with the Generalized Labeled Multi-Bernoulli Filter
Ba Ngu Vo, Ba Tuong Vo
This paper proposes an efficient implementation of the multi-sensor generalized labeled multi-Bernoulli (GLMB) filter. The solution exploits the GLMB joint prediction and update to…
A Generalized Labeled Multi-Bernoulli Filter Implementation using Gibbs Sampling
Hung Gia Hoang, Ba-Tuong Vo, Ba-Ngu Vo
This paper proposes an efficient implementation of the generalized labeled multi-Bernoulli (GLMB) filter by combining the prediction and update into a single step. In contrast to t…