@inproceedings{f4e944a196ca4a3987e0ecb29b08e736,
title = "Labeled Multi-Bernoulli Filter based Group Target Tracking Using SDE and Graph Theory",
abstract = "Multi-target tracking is an extremely challenging task when targets move in the formation of groups and interact with each other. Group target tracking has to deal with this problem in contrast to independently moving targets as assumed in most multi-target tracking algorithms. A feasible approach for group target tracking is to estimate the group structure and modify the motion model in the prediction step of multi-target tracker according to the group structure. In this paper, we propose an ad hoc labeled multi-Bernoulli (LMB) filter for tracking group target with interaction, which use stochastic differential equation to model the joint motion of group targets and estimate group structure by using graph theory. Simulation results show that the proposed algorithm can estimate the target state more accurately than the traditional method without group motion modification.",
keywords = "Graph theory, Group target tracking, LMB filter, Random Finite set (RFS), Stochastic differential equation",
author = "Li Li and Qinchen Wu and Bin Yang and Shaoming Wei and Jun Wang",
note = "Publisher Copyright: {\textcopyright} 2021 International Society of Information Fusion (ISIF).; 24th International Conference on Information Fusion, FUSION 2021 ; Conference date: 01-11-2021 Through 04-11-2021",
year = "2021",
doi = "10.23919/FUSION49465.2021.9626976",
language = "英语",
series = "Proceedings of 2021 IEEE 24th International Conference on Information Fusion, FUSION 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Proceedings of 2021 24th International Conference on Information Fusion, FUSION 2021",
address = "美国",
}