MotionTrack: rethinking the motion cue for multiple object tracking in USV videos

Liang, Zhenqi; Xiao, Gang; Hu, Jianqiu; Wang, Jingshi; Ding, Chunshan

doi:10.1007/s00371-023-02983-y

Cited by 7 publications

(2 citation statements)

References 30 publications

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“…The experimental results show that the proposed method can effectively deal with the problem of ship size change and background interference, and improve the accuracy of ship tracking. Leung et al [13] fully explored motion cues in USV videos and proposed a simple but effective tracker called MotionTrack. The data association of MotionTrack mainly consists of cascade matching with a Gaussian distance module and an observation-centred Kalman filtering module.…”

Section: Discriminative Methodsmentioning

confidence: 99%

A lightweight multi-target ship tracking model based on Yolov7

Cen,

Chen,

Liu

et al. 2024

Phys. Scr.

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Ship multi-target tracking has long been a topic that has attracted researchers from different fields. Currently, the following challenges still exist in ship multi-target tracking. Ships obscuring each other leads to an increase in misdetections and omissions in the algorithm. Some algorithms have a large number of parameters and computations, which are not favourable for deployment into devices. As a result, we present a novel multi-target tracking technique that combines the Yolov7 detector with Kalman filtering. First, the retrieval of fine ship details in the video is accomplished by employing the CNNS(Convolutional Neural Networks) + Transformer + CNNS architecture. Second, we introduce a novel lightweight module known as Light-SPP, which aims to integrate ship features. Finally, Wise-iou Loss, which increases the predictability of ship position, is shown as the detector's localization loss function. The experimental results show that the number of parameters and computation of the model decrease by 11.0% and 17.7% respectively, and the continuous tracking accuracy and tracking and positioning accuracy improve by 17.7% and 7.4% respectively. In summary, our proposed ship multi-target tracking algorithm mainly solves the problems of low tracking accuracy and large computational volume, and has high engineering application prospects in the field of water transport.

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Section: Discriminative Methodsmentioning

confidence: 99%

A lightweight multi-target ship tracking model based on Yolov7

Cen,

Chen,

Liu

et al. 2024

Phys. Scr.

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“…From the point of defense, the new technology of USVs mainly casts light on derivative techniques, combat theories and methods of arrangement in military scenarios. Multiple object tracking (MOT) in USV videos has many application scenarios in the military and civilian fields [111]. By projecting military power in a more affordable way, through the use of USVs, the exposure of human life to military risks should be significantly reduced [112].…”

Section: Navigation Safety and Military Defensementioning

confidence: 99%

A Bibliometric Analysis and Overall Review of the New Technology and Development of Unmanned Surface Vessels

Yang,

Xue,

2024

JMSE

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With the significant role that Unmanned Surface Vessels (USVs) could play in industry, the military and the transformation of ocean engineering, a growing research interest in USVs is attracted to their innovation, new technology and automation. Yet, there has been no comprehensive review grounded in bibliometric analysis, which concentrates on the most recent technological advancements and developments in USVs. To provide deeper insight into the relevant research trends, this study employs a bibliometric analysis to examine the basic features of the literature from 2000 to 2023, and identifies the key research hotspots and modeling techniques by reviewing their current statuses and the recent efforts made in these areas. Based on the analysis of the temporal and spatial trends, disciplines and journals’ distribution, institutions, authors and citations, the publications relating to the new technology of USVs are assessed based on their keywords and the term analysis in the literature; six future research directions are proposed, including enhanced intelligence and autonomy, highly integrated sensor systems and multi-modal task execution, extended endurance and resilience, satellite communication and interconnectivity, eco-friendly and sustainable practices and safety and defense. The scientific literature is reviewed in a systematic way using a comparative analysis of existing tools, and the results greatly contribute to understanding the overall situation of new technology in USVs. This paper is enlightening to students, international scholars and institutions, as it can facilitate partnerships between industry and academia to allow for concerted efforts to be made in the domain of USVs.

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