Advance Intelligent Video Surveillance System (AIVSS): A Future Aspect

Over the last few decades, remarkable infrastructure growths have been noticed in security-related issues throughout the world. So, with increased demand for Security, Video-based Surveillance has become an important area for the research. An Intelligent Video Surveillance system basically censored the performance, happenings, or changing information usually in terms of human beings, vehicles or any other objects from a distance by means of some electronic equipment (usually digital camera). The scopes like prevention, detection, and intervention which have led to the development of real and consistent video surveillance systems are capable of intelligent video processing competencies. In broad terms, advanced video-based surveillance could be described as an intelligent video processing technique designed to assist security personnel’s by providing reliable real-time alerts and to support efficient video analysis for forensic investigations. This chapter deals with the various requirements for designing a robust and reliable video surveillance system. Also, it is discussed the different types of cameras required in different environmental conditions such as indoor and outdoor surveillance. Different modeling schemes are required for designing of efficient surveillance system under various illumination conditions

Co-operative surveillance cameras for high quality face acquisition in a real-time door monitoring system

The increasing number of CCTV cameras in use poses a problem of information overloading for end users. Smart technologies are used in video surveillance to automatically analyze and detect events of interest in real-time, through 2D and 3D video processing techniques called video analytics. This paper presents a smart surveillance stereo vision system for real-time intelligent door access monitoring. The system uses two IP cameras in a stereo configuration and a pan-tilt-zoom (PTZ) camera, to obtain real-time localised, high quality images of any triggering events

Co-operative surveillance cameras for high quality face acquisition in a real-time door monitoring system

The increasing number of CCTV cameras in use poses a problem of information overloading for end users. Smart technologies are used in video surveillance to automatically analyze and detect events of interest in real-time, through 2D and 3D video processing techniques called video analytics. This paper presents a smart surveillance stereo vision system for real-time intelligent door access monitoring. The system uses two IP cameras in a stereo configuration and a pan-tilt-zoom (PTZ) camera, to obtain real-time localised, high quality images of any triggering events

On the design and implementation of a high definition multi-view intelligent video surveillance system

This paper proposes a distributed architecture for high definition (HD) multi-view video surveillance system. It adopts a modular design where multiple intelligent Internet Protocol (IP)-based video surveillance cameras are connected to a local video server. Each server is equipped with storage and optional graphics processing units (GPUs) for supporting high-level video analytics and processing algorithms such as real-time decoding and tracking for the video captured. The servers are connected to the IP network for supporting distributed processing and remote data access. The DSP-based surveillance camera is equipped with realtime algorithms for streaming compressed videos to the server and performing simple video analytics functions. We also developed video analytics algorithms for security monitoring. Both publicly available data set and real video data that are captured under indoor and outdoor scenarios are used to validate our algorithms. Experimental results show that our distributed system can support real-time video applications with high definition resolution.published_or_final_versio

Implementation of Closed-circuit Television (CCTV) Using Wireless Internet Protocol (IP) Camera

This paper presents three techniques for configuring, interfacing and networking of a wireless IP-based camera for real-time security surveillance systems design. The three different real-time implementation techniques proposed for configuring, interfacing and networking the IP camera are: 1). accessing the IP-based camera using the WANSCAM or XXCAM vendor software, 2). accessing the IP-based camera via Firefox® web browser , and 3). accessing the IP camera via MATLAB with SIMULINK on an internet ready system. The live streaming video based on the proposed techniques can be adapted for image detection, recognition and tracking for real-time intelligent security surveillance systems design.  The paper also carried out a thorough comparative analysis of the three methods of achieving video streaming resulting from the output of the IP-based cameras. The analysis shows that the WANSCAM or XXCAM software displays the best video animations from the IP-based cameras when compared with the performance of the other methods. Keywords: Closed-circuit television, Internet protocol, Security surveillance, IP-based cameras, Wireless networking, animation

Evaluation of MoG Video Segmentation on GPU-based HPC System

Automated and intelligent video surveillance systems play an important role in the modern world. Since the number of various video streams that must be analyzed concurrently grows, such systems can assist humans in performing tiresome tasks. In order to be effective, video surveillance systems have to meet several requirements: they must be accurate and able to process the received video stream in real-time. A robust system should not depend on lighting conditions, illumination changes and other sources of scene variation. A common component of surveillance systems is a module that performs background estimation and foreground segmentation. The MoG (Mixture of Gaussians) algorithm is a widely used statistical technique of video segmentation. The estimation process is time-consuming, especially for complex mixture models containing many components. The work presented here focuses on the performance evaluation of MoG algorithm aiming to assess feasibility of OpenCL-based processing of high resolution video on GPU accelerated platforms

AN IP-BASED LIVE DATABASE APPROACH TO SURVEILLANCE APPLICATION DEVELOPMENT

With the proliferation of inexpensive cameras, video surveillance applications are becoming ubiquitous in many domains such as public safety and security, manufacturing, intelligent transportation systems, and healthcare. IP-based video surveillance technologies, in particular, are able to bring traditional video surveillance centers to virtually any computer at any location with an Internet connection. Today’s IP-based video surveillance systems, however, are designed for specific classes of applications. For instance, one cannot use a system designed for incident detection on highways to monitor patients in a healthcare facility. To support rapid development of video surveillance applications, we designed and implemented a new class of general purpose database management system, the live video database management system (LVDBMS). We view networked IP cameras as a special class of storage devices, and allow the user to formulate ad hoc queries expressed over live video feeds. These continuous queries are processed in real time using novel distributed computing techniques. With this environment, the users are able to develop various specific web-based video surveillance systems for a variety of applications. These systems can coexist in a unified LVDBMS framework to share the expensive deployment and operating costs of the camera networks. Our contribution is the introduction of a live database approach to video surveillance software development. In this paper, we describe our prototype and present the live video data model, the query language, and the query processing technique. 1

INTELLIGENT VIDEO SURVEILLANCE OF HUMAN MOTION: ANOMALY DETECTION

Intelligent video surveillance is a system that can highlight extraction and video summarization that require recognition of the activities occurring in the video without any human supervision. Surveillance systems are extremely helpful to guard or protect you from any dangerous condition. In this project, we propose a system that can track and detect abnormal behavior in indoor environment. By concentrating on inside house enviromnent, we want to detect any abnormal behavior between adult and toddler to avoid abusing to happen. In general, the frameworks of a video surveillance system include the following stages: background estimator, segmentation, detection, tracking, behavior understanding and description. We use training behavior profile to collect the description and generate statistically behavior to perform anomaly detection later. We begin with modeling the simplest actions like: stomping, slapping, kicking, pointed sharp or blunt object that do not require sophisticated modeling. A method to model actions with more complex dynamic are then discussed. The results of the system manage to track adult figure, toddler figure and harm object as third subject. With this system, it can bring attention of human personnel security. For future work, we recommend to continue design methods for higher level representation of complex activities to do the matching anomaly detection with real-time video surveillance. We also propose the system to embed with hardware solution for triggered the matching detection as output