Multi-Sensor Surveillance System Based on Integrated Video Analytics

Purohit, Manoj; Singh, Manvendra K.; Yadav, Saralesh; Singh, Adarsh Kumar; Kumar, Ajay; Kaushik, Brajesh Kumar

doi:10.1109/jsen.2021.3131579

Cited by 11 publications

(3 citation statements)

References 80 publications

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“…As the integration of these systems becomes increasingly pervasive, a paramount concern has emerged regarding the security of surveillance video transmissions, prompting the need for sophisticated and resilient solutions. Surveillance technologies, often shrouded in secrecy for operational efficiency [3], encounter distinct challenges, both in wired and wireless domains. Wired surveillance cameras, despite their discreet nature, are susceptible to exposure through the existence of signal lines [4].…”

Section: Introductionmentioning

confidence: 99%

Covert Surveillance Video Transmission with QAM Constellations Modulation

Qiao,

Liu,

et al. 2024

Applied Sciences

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This study explores the covert transmission of surveillance videos using QAM (quadrature amplitude modulation) constellations. By analyzing transmission strategies used in surveillance video systems, we adopt KL divergence as the constraint for covertness performance and mutual information to characterize transmission rates. Utilizing the Taylor series expansion method, we simplify the complex integral calculations of mutual information and KL divergence into summation operations. This simplification not only reduces computational complexity but also ensures precise calculations. Theoretical derivations establish the necessary conditions for the covert transmission of surveillance videos, optimizing modulation probabilities for constellation points. Experimental results and simulation validations demonstrate the superior performance of our proposed method in terms of both information transfer and precision.

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Section: Introductionmentioning

confidence: 99%

Covert Surveillance Video Transmission with QAM Constellations Modulation

Qiao,

Liu,

et al. 2024

Applied Sciences

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“…For example, to improve the crime prevention function in cities, increasing numbers of surveillance cameras are being installed [4,5]. To enhance surveillance camera system functionality, topics such as multi-camera integration [6,7] and drone surveillance with non-fixed camera location [8,9] are being studied. Surveillance cameras in commercial establishments are also being used for marketing purposes.…”

Section: Introductionmentioning

confidence: 99%

Calibration‐Free Height Estimation for Person

Takeda,

Bandoh,

Kitahara

et al. 2024

IEEJ Transactions Elec Engng

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Demand for use of indoor and outdoor surveillance cameras to prevent crime, analyze customer behavior in commercial facilities and other purposes has been increasing. For these types of applications, it is important to be able to estimate information that cannot be observed directly from the images, using the image data. One such type of information is the height of people appearing in the video. People's heights can be used, for example, to help identify a suspect in a crime investigation or as an attribute to understand customers better for marketing. However, many conventional technologies for estimating height from images have required special calibration, or the acquisition of other information in addition to the video. This paper proposes a method for estimating a person's height using only an image, without the need for any special calibration. The key points of the proposed method involve the following two processes. In the first process, a reference object of known size and the person are recognized and the person's height is estimated based on the relative sizes of the person and reference object in the image. The second process involves selecting frames from the video that are appropriate for use in the estimation process. In practical experiments using real video, the method was able to estimate people's heights with an average estimation error of 1.9%. © 2024 The Authors. IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

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“…1) Multiple PTZ cameras can compute the control input for target tracking in a distributed manner; 2) Each camera agent can appropriately track the assigned target through communication from the neighboring camera agents even when the target is temporarily out of the filed of view; 3) The modeling uncertainty of the camera dynamics is compensated by the Gaussian process regression and robust tracking can be guaranteed for unknown bounded disturbance; 4) The proposed method can be applied to automatic surveillance and monitoring such as multi-person tracking for public safety by a distributed multi-camera systems [34], [35].…”

Section: Introductionmentioning

confidence: 99%

Cooperative Target Tracking by Multiagent Camera Sensor Networks via Gaussian Process

2022

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In this paper, we present learning-based robust cooperative control for camera sensor networks. The dynamics of each camera agent with the pan and tilt mechanism is modeled by the Euler-Lagrange equation. In the target tracking problem, the modeling errors caused by high nonlinearity of camera system dynamics and changes in the tracking environment may incur significant deterioration of tracking performance. To address this, we propose a distributed control method based on the Gaussian process regression to compensate for the model uncertainty of the dynamics of the camera sensor network. We consider the error dynamics of the multiagent Euler-Lagrange system to evaluate the tracking errors of the camera agents. We show that the ultimate boundedness of the error dynamics is achieved by the proposed learning-based method. A numerical example confirms that the proposed control law enables each camera agent to track the targets with a bounded tracking error in the presence of model uncertainty.

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Multi-Sensor Surveillance System Based on Integrated Video Analytics

Cited by 11 publications

References 80 publications

Covert Surveillance Video Transmission with QAM Constellations Modulation

Covert Surveillance Video Transmission with QAM Constellations Modulation

Calibration‐Free Height Estimation for Person

Cooperative Target Tracking by Multiagent Camera Sensor Networks via Gaussian Process

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