An Experiment for Detection of Underwater Intruders with Different Kinds of Sensors

Stiller, Dietmar; Benen, Stephan; Berkel, Paula

doi:10.1007/978-3-642-33161-9_49

Cited by 3 publications

(2 citation statements)

References 2 publications

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“…The research, as discussed in this paper, is concerned with the detection of a cooperative human diver, while previous work in diver detection has often been associated with the detection of adversarial forces in harbors or sensitive military locations [2] [3]. However, researchers at McGill University have used frequency analysis in video data to detect the periodic motion of a cooperating human diver's fins.…”

Section: A Related Workmentioning

confidence: 97%

Sonar-Based Detection and Tracking of a Diver for Underwater Human-Robot Interaction Scenarios

DeMarco

West

Howard

2013

2013 IEEE International Conference on Systems, Man, and Cybernetics

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An underwater robotic assistant could help a human diver by illuminating work areas, fetching tools from the surface, or monitoring the diver's activity for abnormal behavior. However, in order for basic Underwater Human-Robot Interaction (UHRI) to be successful, the robotic assistant has to first be able to detect and track the diver. This paper discusses the detection and tracking of a diver with a high-frequency forwardlooking sonar. The first step in the diver detection involves utilizing classical 2D image processing techniques to segment moving objects in the sonar image. The moving objects are then passed through a blob detection algorithm, and then the blob clusters are processed by the cluster classification process. Cluster classification is accomplished by matching observed cluster trajectories with trained Hidden Markov Models (HMM), which results in a cluster being classified as either a diver or clutter. Real-world results show that a moving diver can be autonomously distinguished from stationary objects in a noisy sonar image and tracked.

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Section: A Related Workmentioning

confidence: 97%

Sonar-Based Detection and Tracking of a Diver for Underwater Human-Robot Interaction Scenarios

DeMarco

West

Howard

2013

2013 IEEE International Conference on Systems, Man, and Cybernetics

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“…With the characteristics of small size, high maneuverability, and difficult to detect, diver attack is a common means used by terrorist organization to attack navy vessels base, offshore platform, civil harbor, and so on [1,2]. erefore, many countries and organizations have made great efforts for diver detection.…”

Section: Introductionmentioning

confidence: 99%

Saliency-Based Diver Target Detection and Localization Method

Zhu

Gao

et al. 2020

Mathematical Problems in Engineering

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Diver target automatic detection is indispensable for underwater defense systems, such as the unmanned harbor surveillance system. It is a very challenging task due to various poses and intensity features of diver target. In addition, the background noise in sonar images is complex, which also makes the task more difficult. In this paper, we propose a diver detection method based on saliency detection for sonar images. On the basis of studying the characteristics of diver sonar images, we first decompose the original sonar image and perform median filtering on it, which can significantly improve the quality of the sonar image saliency map. We employ saliency detection technique based on frequency analysis to segment the acoustic highlight region from its surroundings. This segmentation region roughly locates the diver target and generates a region of interest (ROI). We then extract the acoustic shadow region in ROI, which contributes to furtherly improve the localization accuracy. Finally, we merge the segmented highlight region and the extracted acoustic shadow region and compute the minimum outer rectangle of the merged region. Experimental results validate that the proposed method can well detect and locate the diver target, and it can also satisfy the demands of real-time application, and there is almost no false alarm in this method.

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Classifying objects in 2D imaging sonar via tracking of diver fins

DeMarco

Howard

2016

OCEANS 2016 MTS/IEEE Monterey

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An Experiment for Detection of Underwater Intruders with Different Kinds of Sensors

Cited by 3 publications

References 2 publications

Sonar-Based Detection and Tracking of a Diver for Underwater Human-Robot Interaction Scenarios

Sonar-Based Detection and Tracking of a Diver for Underwater Human-Robot Interaction Scenarios

Saliency-Based Diver Target Detection and Localization Method

Classifying objects in 2D imaging sonar via tracking of diver fins

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