Intelligent video surveillance for real time energy savings in smart buildings using HEVC compressed domain features

2018 ◽  
Vol 77 (21) ◽  
pp. 29059-29076 ◽  
Author(s):  
Devesh Samaiya ◽  
Karunesh Kumar Gupta
Keyword(s):  
Real Time ◽  
Video Surveillance ◽  
Energy Savings ◽  
Compressed Domain ◽  
Intelligent Video Surveillance ◽  
Smart Buildings

scholarly journals SIAT: A Distributed Video Analytics Framework for Intelligent Video Surveillance

Symmetry ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 911 ◽  
Author(s):  
Md Azher Uddin ◽  
Aftab Alam ◽  
Nguyen Anh Tu ◽  
Md Siyamul Islam ◽  
Young-Koo Lee
Keyword(s):  
Distributed Computing ◽  
Real Time ◽  
Video Surveillance ◽  
Video Processing ◽  
Large Scale ◽  
Distributed Processing ◽  
Content Management ◽  
Video Data ◽  
Video Analytics ◽  
Intelligent Video Surveillance

In recent years, the amount of intelligent CCTV cameras installed in public places for surveillance has increased enormously and as a result, a large amount of video data is produced every moment. Due to this situation, there is an increasing request for the distributed processing of large-scale video data. In an intelligent video analytics platform, a submitted unstructured video undergoes through several multidisciplinary algorithms with the aim of extracting insights and making them searchable and understandable for both human and machine. Video analytics have applications ranging from surveillance to video content management. In this context, various industrial and scholarly solutions exist. However, most of the existing solutions rely on a traditional client/server framework to perform face and object recognition while lacking the support for more complex application scenarios. Furthermore, these frameworks are rarely handled in a scalable manner using distributed computing. Besides, existing works do not provide any support for low-level distributed video processing APIs (Application Programming Interfaces). They also failed to address a complete service-oriented ecosystem to meet the growing demands of consumers, researchers and developers. In order to overcome these issues, in this paper, we propose a distributed video analytics framework for intelligent video surveillance known as SIAT. The proposed framework is able to process both the real-time video streams and batch video analytics. Each real-time stream also corresponds to batch processing data. Hence, this work correlates with the symmetry concept. Furthermore, we introduce a distributed video processing library on top of Spark. SIAT exploits state-of-the-art distributed computing technologies with the aim to ensure scalability, effectiveness and fault-tolerance. Lastly, we implant and evaluate our proposed framework with the goal to authenticate our claims.

A Brief Cartography of Smart Cameras

2011 ◽  
pp. 257-271
Author(s):  
Fernanda Bruno
Keyword(s):  
Real Time ◽  
Video Surveillance ◽  
Urban Space ◽  
Automated Detection ◽  
Surveillance Systems ◽  
Smart Cameras ◽  
Intelligent Video Surveillance ◽  
Individual Level ◽  
Future Events ◽  
Control Devices

This chapter carries out a brief cartography of the so-called “intelligent” video surveillance systems. These systems are programmed to accomplish real time automated detection of situations considered irregular and/or suspicious in specific environments, in order to predict and prevent undesirable events. Three aspects of the smart cameras are focused in this cartography. First, the author explores its regime of visibility and note how it prioritizes the capture of irregularities in the body’s movements in urban space. Second, the author shows how the type of monitoring and profiling of bodies and behaviors in these systems generally acts at the visible, surface and infra-individual level of human conduct. Finally, he analyzes the temporality of smart cameras, especially in its proactive dimension that intends to foresee and intervene, in real time, in future events. The analysis of these three aspects of the intelligent video surveillance identifies and highlights discourses, processes and operations that are common to the exercising of power and surveillance in contemporary societies – more specifically, those which are included in the realm of control devices.

A Brief Cartography of Smart Cameras

2013 ◽  
pp. 66-80
Author(s):  
Fernanda Bruno
Keyword(s):  
Real Time ◽  
Video Surveillance ◽  
Urban Space ◽  
Automated Detection ◽  
Surveillance Systems ◽  
Smart Cameras ◽  
Intelligent Video Surveillance ◽  
Individual Level ◽  
Future Events ◽  
Control Devices

This chapter carries out a brief cartography of the so-called “intelligent” video surveillance systems. These systems are programmed to accomplish real time automated detection of situations considered irregular and/or suspicious in specific environments, in order to predict and prevent undesirable events. Three aspects of the smart cameras are focused in this cartography. First, the author explores its regime of visibility and note how it prioritizes the capture of irregularities in the body’s movements in urban space. Second, the author shows how the type of monitoring and profiling of bodies and behaviors in these systems generally acts at the visible, surface and infra-individual level of human conduct. Finally, he analyzes the temporality of smart cameras, especially in its proactive dimension that intends to foresee and intervene, in real time, in future events. The analysis of these three aspects of the intelligent video surveillance identifies and highlights discourses, processes and operations that are common to the exercising of power and surveillance in contemporary societies – more specifically, those which are included in the realm of control devices.

A real-time wavelet-based video compression approach to intelligent video surveillance systems

2006 ◽  
Vol 25 (1) ◽  
pp. 50 ◽  
Author(s):  
Bing-Fei Wu ◽  
Yen-Lin Chen ◽  
Chao-Jung Chen ◽  
Chung-Cheng Chiu ◽  
Chorng-Yann Su
Keyword(s):  
Real Time ◽  
Video Compression ◽  
Video Surveillance ◽  
Surveillance Systems ◽  
Intelligent Video Surveillance

Application of Non-Parametric Kernel Density Background Modeling Method in Intelligent Video Surveillance System

2015 ◽  
Vol 799-800 ◽  
pp. 1117-1120
Author(s):  
Ying Zhang ◽  
Meng Xin Li ◽  
Jing Hou
Keyword(s):  
Real Time ◽  
Video Surveillance ◽  
Surveillance System ◽  
Kernel Density ◽  
Low Noise ◽  
Video Surveillance System ◽  
Intelligent Video Surveillance ◽  
Time Performance ◽  
Intelligent Video Surveillance System ◽  
Non Parametric

Aiming to get better real time performance and effect of detection in dynamic scene of intelligent video surveillance system, non-parametric kernel density estimation (KDE) is used to model the background. And to solve the foreground detection is not precise enough, background subtraction method is fused to detect the foreground. And some modified work is done to suppress shadow and noise. Experiments show that the method proposed can get better real time performance and low noise detect result in intelligent video surveillance system.

scholarly journals Intelligent video surveillance for real-time detection of suicide attempts

2018 ◽  
Vol 110 ◽  
pp. 1-7 ◽  
Author(s):  
Wassim Bouachir ◽  
Rafik Gouiaa ◽  
Bo Li ◽  
Rita Noumeir
Keyword(s):  
Real Time ◽  
Video Surveillance ◽  
Suicide Attempts ◽  
Intelligent Video Surveillance ◽  
Real Time Detection
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