A New Networked Surveillance Video System by Combination of Omni-Directional and Network Controlled Cameras

Sato, Yukiya; Hashimoto, Koji; Shibata, Yoshitaka

doi:10.1007/978-3-540-85693-1_33

Cited by 7 publications

(5 citation statements)

References 2 publications

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“…On the other hands, there is an example that Pan-TiltZoom (PTZ) cameras are used instead of CCD cameras [1]. One of the benefits of PTZ camera is that it can reduce blind spots by turning the camera lens, and that it can also provide the wide range of the observation angle.…”

Section: Introductionmentioning

confidence: 99%

Wide Area Seamless Surveillance Video System to Recognize and Track Moving Objects Based on Gigabit Network

Shibata

Kon

Uchida

et al. 2013

2013 IEEE 27th International Conference on Advanced Information Networking and Applications (AINA)

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Recently, a surveillance system has been widely used for our circumstances for the purpose of observing volcano, tsunami, crime prevention, and so on. However, most of surveillance systems are consisted of handy cameras and mono-directional CCD cameras, and so it is caused "blind spot" on the system. In this paper, Omni-directional lens is introduced for Gigabit Ether Camera, and the Seamless Surveillance Video System with high-speed networks and high-resolution Omni-directional cameras is proposed. The proposed system also has the additional functions such as moving detections, recognitions, and object's tracking.The paper discussed about the implementation and evaluation of the proposed system.

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Section: Introductionmentioning

confidence: 99%

Wide Area Seamless Surveillance Video System to Recognize and Track Moving Objects Based on Gigabit Network

Shibata

Kon

Uchida

et al. 2013

2013 IEEE 27th International Conference on Advanced Information Networking and Applications (AINA)

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“…Due to their restricted field of view, PTZ cameras present some limitations that can be overcome by using 360 • panoramic image capture devices. These devices supply different sorts of 360 • spherical images offering the possibility of covering most of the monitored area on each video frame as it is described in works like [17] and [18]. This sort of systems have been in continuous improvement by scientists and engineers, reaching high performance levels in object detection and tracking as it is described in [19].…”

Section: Introductionmentioning

confidence: 99%

Deep learning-based anomalous object detection system for panoramic cameras managed by a Jetson TX2 board

Benito-Picazo

Domínguez

Palomo

et al. 2021

2021 International Joint Conference on Neural Networks (IJCNN)

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Social conflicts appearing in the media are increasing public awareness about security issues, resulting in a higher demand of more exhaustive environment monitoring methods. Automatic video surveillance systems are a powerful assistance to public and private security agents. Since the arrival of deep learning, object detection and classification systems have experienced a large improvement in both accuracy and versatility. However, deep learning-based object detection and classification systems often require expensive GPU-based hardware to work properly. This paper presents a novel deep learning-based foreground anomalous object detection system for video streams supplied by panoramic cameras, specially designed to build power efficient video surveillance systems. The system optimises the process of searching for anomalous objects through a new potential detection generator managed by three different multivariant homoscedastic distributions. Experimental results obtained after its deployment in a Jetson TX2 board attest the good performance of the system, postulating it as a solvent approach to power saving video surveillance systems.

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“…In the normal case, the proposed system is also used for natural environmental surveillance of road conditions such as rainfall, snow covers and flooded rivers even though the challenged network environments hilly and mountainous areas [1] [2][3] [4].…”

Section: Introductionmentioning

confidence: 99%

SODiCS on Challenged Communication Environment

Ito

Hirakawa²,

Shibata

2014

2014 Eighth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing

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Through we experienced at the Eastern Japan Great Earthquake on March 11, 2011, a disaster information gathering systems are strongly needed to widely collect the disaster state around the evaluated areas, correctly analyze the degree of damages and quickly make decision of disaster recovery response. For this requirement, a mobile video surveillance system on a vehicle based on wireless network is useful on because of its wide rage monitoring and mobility. However, since most of the communication lines and systems are seriously damaged and the communication state is widely worse particularly in hilly and mountainous areas. In this paper, we introduce SODiCS (Spatial and Temporal Omnidirectional Video Distribution and Collection System) for challenged communication environment. Video data gathered using omnidirectional camera and various sensors are transmitted to all of the users through a web application. The user can see those collected data on GIS map as a web application. We developed the system with two modes as video distribution functions, Live View mode and Storage View mode. The system configuration and architecture are explained and a prototype system is constructed to evaluate the performance of our system.

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A New Networked Surveillance Video System by Combination of Omni-Directional and Network Controlled Cameras

Cited by 7 publications

References 2 publications

Wide Area Seamless Surveillance Video System to Recognize and Track Moving Objects Based on Gigabit Network

Wide Area Seamless Surveillance Video System to Recognize and Track Moving Objects Based on Gigabit Network

Deep learning-based anomalous object detection system for panoramic cameras managed by a Jetson TX2 board

SODiCS on Challenged Communication Environment

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