Video Surveillance System Applications

2014 ◽  
pp. 311-333
Keyword(s):  
Video Surveillance ◽  
Surveillance System ◽  
Video Transmission ◽  
Digital Transmission ◽  
Design Guidelines ◽  
Video Surveillance System ◽  
Recording Technology ◽  
Video Signals ◽  
Effective System ◽  
Schedule Type

The fact that video surveillance is such an effective system especially when one thinks of its widespread use attests to its low investment cost. This chapter contains information about design guidelines, hardware information, specific examples, and necessary parameters to be addressed while designing representative security video surveillance system applications: protection of all assets and personnel, calculation of the overall cost of the video system, surveillance target (assets and/or personnel), surveillance timing schedule, type and number of cameras needed, camera placement, field of view required, console room monitoring equipment, number and types of monitors, number of displays per monitor, number and type of recorders, digital recording technology needed, type of video switchers, type of video printer, if additional lighting is required, if intensified or thermal IR cameras are required, if sensors at doors, windows, and perimeters that are integrated with video signals are needed, digital video motion detectors placement, IP cameras, type of signal and video transmission, type of digital transmission, type of 802.11 protocol, type of compression (MPEG-4 or H.264), and the necessity of encryption or scrambling.

Research and Implementation of RTP/RTCP in Mobile Video Surveillance System

2014 ◽  
Vol 926-930 ◽  
pp. 2521-2524
Author(s):  
Han Cao ◽  
Hao Zeng ◽  
Yang Fu
Keyword(s):  
Video Compression ◽  
Video Surveillance ◽  
Packet Loss ◽  
Surveillance System ◽  
Video Transmission ◽  
Transmission Rate ◽  
Video Data ◽  
Video Surveillance System ◽  
Mobile Video ◽  
Transmission Method

As people for the need on more security, traditional fixed video surveillance cannot satisfied with people’s varying requirements. This paper demonstrates the framework of a set of mobile video surveillance which support CDMA2000/TD-SCDMA/WCDMA network, RTP protocol is chosen as the transport protocol and H.264 is chosen as the video compression standard. Select RTCP protocol gather packet loss fraction parameter that controls the transmission rate of RTP traffic. We analyze RTP/RTCP protocol and media data transmission process in video surveillance system; discuss the current video transmission method in video surveillance system, the problem of packet loss while transporting video data, and extract packet process of RTP packet.

A Scheme Based on Embedded Processor for Network Video Surveillance System

2014 ◽  
Vol 687-691 ◽  
pp. 3485-3488
Author(s):  
S.M. Wang ◽  
W. Yao ◽  
M.X. Yan ◽  
G.Z. Wen
Keyword(s):  
Real Time ◽  
Video Surveillance ◽  
Surveillance System ◽  
Video Surveillance System ◽  
Network Resources ◽  
Web Browser ◽  
Embedded Processor ◽  
Video Signals ◽  
Usb Camera ◽  
Network Camera

A scheme based on 32-bits S3C2440 of ARM920T and Linux OS for network video surveillance system is proposed. The video signals are collected by a USB camera and are coded by H264. The data are then transported to the network by a standard Ethernet port and are displayed by a WEB server. The network camera has an independent IP. Remote users could dispatch and browse the whole network resources to achieve real-time monitoring with their PC standard web browser.

A Video Surveillance System for Monitoring the Endangered Mediterranean Monk Seal (Monachus monachus)

2007 ◽  
Vol 33 (2) ◽  
pp. 179-184 ◽  
Author(s):  
Panagiotis Dendrinos ◽  
Eleni Tounta ◽  
Alexandros A. Karamanlidis ◽  
Anastasios Legakis ◽  
Spyros Kotomatas
Keyword(s):  
Video Surveillance ◽  
Surveillance System ◽  
Video Surveillance System

scholarly journals Secure Video Surveillance Framework in Smart City

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4419
Author(s):  
Hao Li ◽  
Tianhao Xiezhang ◽  
Cheng Yang ◽  
Lianbing Deng ◽  
Peng Yi
Keyword(s):  
Video Surveillance ◽  
Smart City ◽  
Key Management ◽  
Surveillance System ◽  
Chinese Remainder Theorem ◽  
Smart Cities ◽  
Group Key Management ◽  
Video Surveillance System ◽  
Surveillance Systems ◽  
Key Update

In the construction process of smart cities, more and more video surveillance systems have been deployed for traffic, office buildings, shopping malls, and families. Thus, the security of video surveillance systems has attracted more attention. At present, many researchers focus on how to select the region of interest (RoI) accurately and then realize privacy protection in videos by selective encryption. However, relatively few researchers focus on building a security framework by analyzing the security of a video surveillance system from the system and data life cycle. By analyzing the surveillance video protection and the attack surface of a video surveillance system in a smart city, we constructed a secure surveillance framework in this manuscript. In the secure framework, a secure video surveillance model is proposed, and a secure authentication protocol that can resist man-in-the-middle attacks (MITM) and replay attacks is implemented. For the management of the video encryption key, we introduced the Chinese remainder theorem (CRT) on the basis of group key management to provide an efficient and secure key update. In addition, we built a decryption suite based on transparent encryption to ensure the security of the decryption environment. The security analysis proved that our system can guarantee the forward and backward security of the key update. In the experiment environment, the average decryption speed of our system can reach 91.47 Mb/s, which can meet the real-time requirement of practical applications.

scholarly journals Smart Video Surveillance System Based on Edge Computing

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2958
Author(s):  
Antonio Carlos Cob-Parro ◽  
Cristina Losada-Gutiérrez ◽  
Marta Marrón-Romera ◽  
Alfredo Gardel-Vicente ◽  
Ignacio Bravo-Muñoz
Keyword(s):  
Computer Vision ◽  
Video Surveillance ◽  
Surveillance System ◽  
Video Surveillance System ◽  
Smart Camera ◽  
People Detection ◽  
Camera System ◽  
Edge Node ◽  
New Processing ◽  
Processor Unit

New processing methods based on artificial intelligence (AI) and deep learning are replacing traditional computer vision algorithms. The more advanced systems can process huge amounts of data in large computing facilities. In contrast, this paper presents a smart video surveillance system executing AI algorithms in low power consumption embedded devices. The computer vision algorithm, typical for surveillance applications, aims to detect, count and track people’s movements in the area. This application requires a distributed smart camera system. The proposed AI application allows detecting people in the surveillance area using a MobileNet-SSD architecture. In addition, using a robust Kalman filter bank, the algorithm can keep track of people in the video also providing people counting information. The detection results are excellent considering the constraints imposed on the process. The selected architecture for the edge node is based on a UpSquared2 device that includes a vision processor unit (VPU) capable of accelerating the AI CNN inference. The results section provides information about the image processing time when multiple video cameras are connected to the same edge node, people detection precision and recall curves, and the energy consumption of the system. The discussion of results shows the usefulness of deploying this smart camera node throughout a distributed surveillance system.

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