Trajectory multi-Bernoulli filters for multi-target tracking based on sets of trajectories
Paper in proceedings, 2020

This paper presents two multi-Bernoulli filters on sets of trajectories for multiple target tracking. The first filter provides a multi-Bernoulli approximation of the posterior density over the set of alive trajectories at the current time step. The second filter provides a multi-Bernoulli approximation of the posterior density over the set of all trajectories (alive and dead) up to the current time. We also explain the Gaussian implementation of the filters and compare them with other multiple target tracking algorithms in a simulated scenario.

sets of trajectories.

Poisson multi-Bernoulli mixtures

Multiple target tracking

multi-target conjugate priors

Author

Angel Garcia

University of Liverpool

Lennart Svensson

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering, Signal Processing

Jason L. Williams

Commonwealth Scientific and Industrial Research Organisation (CSIRO)

Yuxuan Xia

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering, Signal Processing

Karl Granström

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering, Signal Processing

FUSION 2019 - 22nd International Conference on Information Fusion

9190554

2020 IEEE 23rd International Conference on Information Fusion (FUSION)
Rustenburg, South Africa,

Deep multi-object tracking for ground truth trajectory estimation

VINNOVA, 2018-07-01 -- 2022-06-30.

Areas of Advance

Information and Communication Technology

Transport

Subject Categories

Control Engineering

Signal Processing

Computer Science

DOI

10.23919/FUSION45008.2020.9190554

More information

Latest update

1/5/2021 9