Vision-Based Multiobject Tracking Through UAV Swarm

doi:10.1109/LGRS.2023.3305675

2023-01-01

PRE

DOI：10.1109/LGRS.2023.3305675

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摘要

En 中文

Conventional multisensor multiobject tracking algorithms usually fuse local positions to construct the global situation. However, low-cost cameras that have been widely used in small-scale unmanned aerial vehicles (UAVs) only provide bearing angle measurement but not target positions, which prohibits the application of conventional tracking paradigms. We propose a solution of vision-based multiobject tracking through UAV swarm. Given the videos captured by UAVs and the states of the UAVs, the proposed solution fuses visual and geometry information to tackle three tasks: 1) associating the targets reported by different UAVs; 2) computing the targets' positions in inertial coordinate system; and 3) associating the targets reported at different instants. The effectiveness of the proposed solution is evaluated by offline ablation experiments, field scene experiments, and online closed-loop simulation.

Keyword:

Index Terms-Multiobject tracking

spatial and temporal assignment

unmanned aerial vehicle (UAV) swarm

vision-based tracking

期刊

IEEE Geoscience and Remote Sensing Magazine

IF:

16.4

论文数:

1.0W

被引数:

5.1K

机构

beijing institute of technology

学者数:

5.5W

论文数: 4.0W

被引数: 63

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