DMZoomNet: Improving Object Detection Using Distance Information in Intralogistics Environments

Clavero, Carlos; Patricio, Miguel A.; García, Jesús; Molina, José M.

doi:10.1109/tii.2024.3381795

IEEE Trans. Ind. Inf.

2024

DOI: 10.1109/tii.2024.3381795

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DMZoomNet: Improving Object Detection Using Distance Information in Intralogistics Environments

Carlos Clavero,

Miguel A. Patricio,

Jesús García

et al.

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2024

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Cited by 1 publication

References 28 publications

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Drone Swarm for Distributed Video Surveillance of Roads and Car Tracking

Sánchez Pedroche,

Amigo,

García

et al. 2024

Drones

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This study proposes a swarm-based Unmanned Aerial Vehicle (UAV) system designed for surveillance tasks, specifically for detecting and tracking ground vehicles. The proposal is to assess how a system consisting of multiple cooperating UAVs can enhance performance by utilizing fast detection algorithms. Within the study, the differences in one-stage and two-stage detection models have been considered, revealing that while two-stage models offer improved accuracy, their increased computation time renders them impractical for real-time applications. Consequently, faster one-stage models, such as the tested YOLOv8 architectures, appear to be a more viable option for real-time operations. Notably, the swarm-based approach enables these faster algorithms to achieve an accuracy level comparable to that of slower models. Overall, the experimentation analysis demonstrates how larger YOLO architectures exhibit longer processing times in exchange for superior tracking success rates. However, the inclusion of additional UAVs introduced in the system outweighed the choice of the tracking algorithm if the mission is correctly configured, thus demonstrating that the swarm-based approach facilitates the use of faster algorithms while maintaining performance levels comparable to slower alternatives. However, the perspectives provided by the included UAVs hold additional significance, as they are essential for achieving enhanced results.

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Drone Swarm for Distributed Video Surveillance of Roads and Car Tracking

Sánchez Pedroche,

Amigo,

García

et al. 2024

Drones

View full text Add to dashboard Cite

show abstract

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DMZoomNet: Improving Object Detection Using Distance Information in Intralogistics Environments

Cited by 1 publication

References 28 publications

Drone Swarm for Distributed Video Surveillance of Roads and Car Tracking

Drone Swarm for Distributed Video Surveillance of Roads and Car Tracking

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