Video surveillance is a basic mean for fields monitoring, but in uncertain plots for emergency, it is usually impossible to construct a delivery channel for video surveillance. With the wide spreading of 3G network and smart phones equipped with powerful processor and context-aware sensors, it is possible to build a context-aware based mobile surveillance. This work provided a mobile video surv...

The usefulness of networks of surveillance cameras is primarily limited by the demand placed on human supervisors to monitor many real time video feeds simultaneously. The goal of automated visual surveillance is to reduce the burden on operators by including software in a surveillance system that can analyse video content automatically. This paper reviews progress in the field and considers so...

This paper introduces a new concept for the area of video surveillance called Critical Evidence Snapshot. We show that automatic extraction and annotation of Critical Evidence Snapshots, which are defined as video snapshots that provide a piece of information that is both useful and new, is the key to improving the utility and efficiency of video surveillance systems. An implementation of an AC...

Smart video surveillance is well suited for a broad range of applications. Moving object classification in the field of video surveillance is a key component of smart surveillance software. In this paper, we have proposed reliable software with its large features for people and object classification which works well in challenging real-world constraints, including the presence of shadows, low r...

Video surveillance applications are examples of complex distributed coalition tasks. Real-time capture and analysis of image sensor data is one of the most important tasks in a number of military critical decision making scenarios. In complex battlefield situations, there is a need to coordinate the operation of distributed image sensors and the analysis of their data as transmitted over a hete...

We propose a method for analysis of surveillance video by using low rank and sparse decomposition (LRSD) with low latency combined with compressive sensing to segment the background and extract moving objects in a surveillance video. Video is acquired by compressive measurements, and the measurements are used to analyze the video by a low rank and sparse decomposition of a matrix. The low rank ...

Current video-surveillance systems typically consist of many video sources distributed over a wide area, transmitting live video streams to a central location for processing and monitoring. The target of this paper is to present an experience of implementation of a large-scale video-surveillance system based on a wireless mesh network infrastructure, discussing architecture, protocol, and imple...

In this paper, a video surveillance-based image processing system is developed on Xilinx Spartan3 Field Programmable Gate Array (FPGA) device using embedded development kit (EDK) tools from Xilinx. Two different hardware architectures of two dimensional (2-D) video surveillance have been implemented as a coprocessor in an embedded system. It is direct implementation of video surveillance by Mot...

Video surveillance [1] technology plays an important role in the security field, with its intuitive, convenient and abundant information and is widely used in city traffic, civil security and other various fields especially in the important safety departments or major events. In this paper, according to the video surveillance system features and functional requirements, we use embedded system, ...

This paper reviews papers on tracking people in a video surveillance system, and it presents a new system designed for being able to cope with shadows in a real-time application for counting people which is one of the remaining main problems in adaptive background subtraction in such video surveillance systems. 1 Reveal Ltd., Level 1, Tudor Mall, 333 Remuera Rd, Auckland, New Zealand 2 CITR, De...