Target detection using Gaussian mixture models and fourier transforms for UAV maritime search and rescue

Dinnbier, Nuria Martinez; Thueux, Yoann; Chai, Runqi; Tsourdos, Antonios

doi:10.1109/icuas.2017.7991312

Cited by 16 publications

(5 citation statements)

References 19 publications

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“…(2) Maritime search and rescue scenarios For maritime SAR scenarios, Dinnbier et al proposed a method that combin analysis and frequency pattern recognition using an inexpensive vision camera (E era), which helps to reduce the cost of maritime vision UAV search and rescue [7 Liu et al have invented an intelligently assisted search and rescue system fo in distress in water based on visual perception and computation. This system in multirotor electric UAV flight platform, a base-integrated processing platform, an (2) Maritime search and rescue scenarios For maritime SAR scenarios, Dinnbier et al proposed a method that combines color analysis and frequency pattern recognition using an inexpensive vision camera (EO camera), which helps to reduce the cost of maritime vision UAV search and rescue [77].…”

Section: Application Of Visual Detection and Navigation Technology In...mentioning

confidence: 99%

A Review of Electric UAV Visual Detection and Navigation Technologies for Emergency Rescue Missions

Tang,

Li,

Sun

2024

Sustainability

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Sudden disasters often result in significant losses of human lives and property, and emergency rescue is a necessary response to disasters. In recent years, with the development of electric unmanned aerial vehicles (UAVs) and artificial intelligence technology, the combination of these technologies has been gradually applied to emergency rescue missions. However, in the face of the complex working conditions of emergency rescue missions, the application of electric UAV visual detection still faces great challenges, particularly in relation to a lack of GPS positioning signal in closed emergency rescue environments, as well as unforeseen obstacle avoidance and autonomous planning and searching flights. Although the combination of visual detection and visual navigation technology shows great potential and added value for use in the context of emergency rescue, at present it remains in the research and experimental stages. Consequently, this paper summarizes and discusses the current status and development of visual detection and navigation technologies for electric UAVs, as well as issues related to emergency rescue applications, with a view to accelerating the research and application of visual detection and navigation technologies for electric UAVs in emergency rescue missions. In this study, we first summarize the classification of typical disasters, analyze the application of sample UAV and configurations in typical disasters with a high frequency of occurrence, refine key electric UAV technologies in emergency rescue missions, and propose the value of exploring electric UAV visual detection and navigation technologies. Subsequently, current research on electric UAV visual detection and navigation technology is analyzed and its application in emergency rescue missions is discussed. Finally, this paper presents the problems faced in the application of electric UAV visual detection and navigation technology in urban emergency rescue environments and offers insights into future research directions.

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Section: Application Of Visual Detection and Navigation Technology In...mentioning

confidence: 99%

A Review of Electric UAV Visual Detection and Navigation Technologies for Emergency Rescue Missions

Tang,

Li,

Sun

2024

Sustainability

View full text Add to dashboard Cite

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“…In Dinnbier et al (2017) used Gaussian Mixture Model (GMM) and Fourier Transforms for target detection in UAVs maritime SAR. They not only presented a method to combine…”

Section: Introductionmentioning

confidence: 99%

“…In Dinnbier et al (2017) used Gaussian Mixture Model (GMM) and Fourier Transforms for target detection in UAVs maritime SAR. They not only presented a method to combine color analysis and frequency pattern identification, but also dealt with the dynamically changing background through an adaptive algorithm.…”

Section: Introductionmentioning

confidence: 99%

A detection method of the rescue targets in the marine casualty based on improved YOLOv5s

et al. 2022

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In recent years, with the deep exploitation of marine resources and the development of maritime transportation, ship collision accidents occur frequently, which leads to the increasingly heavy task of maritime Search and Rescue (SAR). Unmanned Aerial Vehicles (UAVs) have the advantages of flexible maneuvering, robust adaptability and extensive monitoring, which have become an essential means and tool for emergency rescue of maritime accidents. However, the current UAVs-based drowning people detection technology has insufficient detection ability and low precision for small targets in high-altitude images. Moreover, limited by the load capacity, UAVs do not have enough computing power and storage space, resulting in the existing object detection algorithms based on deep learning cannot be directly deployed on UAVs. To solve the two issues mentioned above, this paper proposes a lightweight deep learning detection model based on YOLOv5s, which is used in the SAR task of drowning people of UAVs at sea. First, an extended small object detection layer is added to improve the detection effect of small objects, including the extraction of shallow features, a new feature fusion layer and one more prediction head. Then, the Ghost module and the C3Ghost module are used to replace the Conv module and the C3 module in YOLOv5s, which enable lightweight network improvements that make the model more suitable for deployment on UAVs. The experimental results indicate that the improved model can effectively identify the rescue targets in the marine casualty. Specifically, compared with the original YOLOv5s, the improved model mAP@0.5 value increased by 2.3% and the mAP@0.5:0.95 value increased by 1.1%. Meanwhile, the improved model meets the needs of the lightweight model. Specifically, compared with the original YOLOv5s, the parameters decreased by 44.9%, the model weight size compressed by 39.4%, and Floating Point Operations (FLOPs) reduced by 22.8%.

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“…Unmanned aerial vehicles (UAVs) are widely used in photogrammetry, 1 agriculture, 2,3 search and rescue operations, 4 payload transportation, [5][6][7] and target-tracking applications. Recently, UAV-based target-tracking applications have received significant attention, and relevant work has been done to track moving objects visually.…”

Section: Introductionmentioning

confidence: 99%

Bounded distance control for Multi-UAV formation safety and preservation in target-tracking applications

Hegde

Jerry

Ghose

2022

Proceedings of the Institution of Mechanical Engineers, Part G:

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The notion of safety in multi-agent systems assumes great significance in many emerging collaborative multi-robot applications. In this paper, we present a multi-UAV collaborative target-tracking application by defining bounded inter-UAV distances in the formation in order to ensure safe operation. In doing so, we address the problem of prioritizing specific objectives over others in a multi-objective control framework. We propose a barrier Lyapunov function-based distributed control law to enforce the bounds on the distances and assess its Lyapunov stability using a kinematic model. The theoretical analysis is supported by numerical results, which account for measurement noise and moving targets. Straight-line and circular motion of the target are considered, and results for quadratic Lyapunov function-based control, often used in multi-agent multi-objective problems, are also presented. A comparison of the two control approaches elucidates the advantages of our proposed safe-control in bounding the inter-agent distances in a formation. A concluding evaluation using Robot Operating System simulations illustrates the practical applicability of the proposed control to a pair of multi-rotors visually estimating and maintaining their mutual separation within specified bounds, as they track a moving target.

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Target detection using Gaussian mixture models and fourier transforms for UAV maritime search and rescue

Cited by 16 publications

References 19 publications

A Review of Electric UAV Visual Detection and Navigation Technologies for Emergency Rescue Missions

A Review of Electric UAV Visual Detection and Navigation Technologies for Emergency Rescue Missions

A detection method of the rescue targets in the marine casualty based on improved YOLOv5s

Bounded distance control for Multi-UAV formation safety and preservation in target-tracking applications

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