scholarly journals A Novel Framework for Anomaly Detection in Video Surveillance using Convolutional LSTM

2020 ◽  
Vol 9 (4) ◽  
pp. 355-359
Keyword(s):  
Object Tracking ◽  
Video Surveillance ◽  
Event Detection ◽  
Video Data ◽  
Surveillance Systems ◽  
Abnormal Event Detection ◽  
Suggested Approach ◽  
Processing Technologies ◽  
Safety Requirements ◽  
Convolutional Lstm

Today, due to public safety requirements, surveillance systems have gained increased attention. Video data processing technologies such as the identification of activity [1], object tracking [2], crowd counting [3], and the detection of anomalies [ 4] have therefore been rapidly developing. In this study, we establish an unattended method for the detection of anomaly events in videos based on a ConvLSTM encoder-decoder to learn about the evolution of spatial characteristics. Our model only covers typical video events during preparation, whereas in testing the videos are both usual and abnormal. Experiments on the UCSD datasets confirm the validity of the suggested approach to abnormal event detection.

An Intelligent Traffic Engineering Method over Software Defined Networks for Video Surveillance Systems Based on Artificial Bee Colony

2016 ◽  
Vol 12 (4) ◽  
pp. 45-62 ◽  
Author(s):  
Reza Mohammadi ◽  
Reza Javidan
Keyword(s):  
Video Surveillance ◽  
Traffic Engineering ◽  
Surveillance System ◽  
Artificial Bee Colony ◽  
Heuristic Algorithms ◽  
Optimal Solution ◽  
Video Data ◽  
Surveillance Systems ◽  
Bee Colony

In applications such as video surveillance systems, cameras transmit video data streams through network in which quality of received video should be assured. Traditional IP based networks cannot guarantee the required Quality of Service (QoS) for such applications. Nowadays, Software Defined Network (SDN) is a popular technology, which assists network management using computer programs. In this paper, a new SDN-based video surveillance system infrastructure is proposed to apply desire traffic engineering for practical video surveillance applications. To keep the quality of received videos adaptively, usually Constraint Shortest Path (CSP) problem is used which is a NP-complete problem. Hence, heuristic algorithms are suitable candidate for solving such problem. This paper models streaming video data on a surveillance system as a CSP problem, and proposes an artificial bee colony (ABC) algorithm to find optimal solution to manage the network adaptively and guarantee the required QoS. The simulation results show the effectiveness of the proposed method in terms of QoS metrics.

scholarly journals A Face Image Virtualization Mechanism for Privacy Intrusion Prevention in Healthcare Video Surveillance Systems

Symmetry ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 891 ◽  
Author(s):  
Jinsu Kim ◽  
Namje Park
Keyword(s):  
Video Surveillance ◽  
Visual Information ◽  
Face Image ◽  
Video Data ◽  
Surveillance Systems ◽  
Image Information ◽  
Video Information ◽  
Face Area ◽  
Blockchain Technology ◽  
Wide Range

Closed-circuit television (CCTV) and video surveillance systems (VSSs) are becoming increasingly more common each year to help prevent incidents/accidents and ensure the security of public places and facilities. The increased presence of VSS is also increasing the number of per capita exposures to CCTV cameras. To help protect the privacy of the exposed objects, attention is being drawn to technologies that utilize intelligent video surveillance systems (IVSSs). IVSSs execute a wide range of surveillance duties—from simple identification of objects in the recorded video data, to understanding and identifying the behavioral patterns of objects and the situations at the incident/accident scenes, as well as the processing of video information to protect the privacy of the recorded objects against leakage. Besides, the recorded privacy information is encrypted and recorded using blockchain technology to prevent forgery of the image. The technology herein proposed (the “proposed mechanism”) is implemented to a VSS, where the mechanism converts the original visual information recorded on a VSS into a similarly constructed image information, so that the original information can be protected against leakage. The face area extracted from the image information is recorded in a separate database, allowing the creation of a restored image that is in perfect symmetry with the original image for images with virtualized face areas. Specifically, the main section of this study proposes an image modification mechanism that inserts a virtual face image that closely matches a predetermined similarity and uses a blockchain as the storage area.

Design and Implementation of a Prototype Cloud Video Surveillance System

2014 ◽  
Vol 18 (1) ◽  
pp. 40-47 ◽  
Author(s):  
Yong-Hua Xiong ◽  
◽  
Shao-Yun Wan ◽  
Yong He ◽  
Dan Su
Keyword(s):  
Cloud Computing ◽  
Video Surveillance ◽  
Surveillance System ◽  
Distributed Storage ◽  
Video Data ◽  
Video Surveillance System ◽  
Surveillance Systems ◽  
Campus Network ◽  
Design And Implementation ◽  
Cloud Computing Service

Cloud-based video surveillance systems, as a new cloud computing service model, are an emerging research topic, both at home and abroad. Current research is mainly focused on exploring applications of the system. This paper proposes a design and implementation method for cloud-based video surveillance systems using the characteristics of cloud computing, such as parallel computing, large storage space, and easy expandability. The system architecture and function modules are built, and a prototype cloud-based video surveillance system is established in a campus network using key technologies, including virtual machine task access control, video-data distributed storage, and database-active communicationmethods. Using the system, the user is able to place a webcam in a location that requires monitoring so that video surveillance can be achieved, and video data can be viewed through a browser. The system has the following advantages: low investment and maintenance cost, high portability, easily extendable, superior data security, and excellent sharing. As a private cloud server in the campus network, the system is able to not only provide convenient video surveillance services, but it can also be an excellent practical experimental platform for cloud computing-related research, which carries outstanding application value.

scholarly journals Development of a Method of Terahertz Intelligent Video Surveillance Based on the Semantic Fusion of Terahertz and 3D Video Images

2019 ◽  
pp. 134-143 ◽  
Author(s):  
A A Morozov ◽  
O S Sushkova ◽  
I A Kershner ◽  
A F Polupanov
Keyword(s):  
Video Surveillance ◽  
First Generation ◽  
Semantic Content ◽  
3D Video ◽  
Video Data ◽  
The Body ◽  
Video Image ◽  
Surveillance Systems ◽  
Public Places ◽  
Video Images

The terahertz video surveillance opens up new unique opportunities in the field of security in public places, as it allows to detect and thus to prevent usage of hidden weapons and other dangerous items. Although the first generation of terahertz video surveillance systems has already been created and is available on the security systems market, it has not yet found wide application. The main reason for this is in that the existing methods for analyzing terahertz images are not capable of providing hidden and fully-automatic recognition of weapons and other dangerous objects and can only be used under the control of a specially trained operator. As a result, the terahertz video surveillance appears to be more expensive and less efficient in comparison with the standard approach based on the organizing security perimeters and manual inspection of the visitors. In the paper, the problem of the development of a method of automatic analysis of the terahertz video images is considered. As a basis for this method, it is proposed to use the semantic fusion of video images obtained using different physical principles, the idea of which is in that the semantic content of one video image is used to control the processing and analysis of another video image. For example, the information about 3D coordinates of the body, arms, and legs of a person can be used for analysis and proper interpretation of color areas observed on a terahertz video image. Special means of the object-oriented logic programming are developed for the implementation of the semantic fusion of the video data, including special built-in classes of the Actor Prolog logic language for acquisition, processing, and analysis of video data in the visible, infrared, and terahertz ranges as well as 3D video data.

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