SIP在视频监控系统中的应用

文中针对传统视频监控系统中信令协议的缺点,提出了基于SIP协议的分布式视频监控系统的结构体系.并且在简单介绍SIP协议的基础上,对SIP在监控系统中的扩展做出了详细的描述.     

用VC++开发数字视频监控录像系统

视频监控系统是以计算机为核心，结合多媒体技术、计算机网络技术的一种监控主机系统，本文介绍了数字视频监控录像系统，对其主机软件部分多路监视，动态监测和视频压缩，传输等几个模块的编程实现进行详细的讨论。     

An improved surveillance video synopsis framework: a HSATLBO optimization approach

Video surveillance cameras capture huge amount of data 24 hours a day. However, most of these videos contain redundant data which make the process difficult for browsing and analysis. A significant amount of research findings have been made in summarization of recorded video, but such schemes do not have much impact on video surveillance applications. On the contrary, video synopsis is a smart technology that preserves all the activities of every single object and projects them concurrently in a condensed time. The energy minimization module in video synopsis framework plays a vital role, which in turn minimizes the activity loss, number of collision and temporal consistency cost. In most of the reported schemes, Simulated Annealing (SA) algorithm is employed to solve the energy minimization problem. However, it suffers from slow convergence rate resulting in a high computational load to the system. In order to mitigate this issue, this article presents an improved energy minimization scheme using hybridization of SA and Teaching Learning based Optimization (TLBO) algorithms. The suggested framework for static surveillance video synopsis generation consists of four computational modules, namely, Object detection and segmentation, Tube formation, Optimization, and finally Stitching and the central focus is on the optimization module. Thus, the present work deals with an improved hybrid energy minimization problem to achieve global optimal solution with reduced computational time. The motivation behind hybridization (HSATLBO) is that TLBO algorithm has the ability to search rigorously, ensuring to reach the optimum solution with less computation. On the contrary, SA reaches the global optimum solution, but it may get disarrayed and miss some critical search points. Exhaustive experiments are carried out and results compared with that of benchmark schemes in terms of minimizing the activity, collision and temporal consistency costs. All the experiments are conducted on five widely used videos taken from standard surveillance video data set (PETS 2001, MIT Surveillance Dataset, ChangeDetection.Net, PETS 2006 and UMN Dataset) as well as one real generated surveillance video from the IIIT Bhubaneswar Surveillance Dataset. To make a fair comparison, additionally, performance of the proposed hybrid scheme to solve video synopsis optimization problem is also compared with that of the other benchmark functions. Experimental evaluation and analysis confirm that the proposed scheme outperforms other state-of-the-art approaches. Finally, the suggested scheme can be easily and reliably deployed in the off-line video synopsis generation.

     

Jini技术在视频监控中的应用

视频监控系统在现实生活中应用极其广泛,但因为视频监控系统现场设备众多、设备的互异性较大、可扩展性较差的特点,本文构建出一个以Jini体系架构为基础、以服务为核心分布式系统,以使各种视频监控设备均能方便地加入和退出系统,实现设备的"网络即插即用"功能。     

网络视频监控系统中文件系统的设计与实现

本文针对网络视频监控系统中连续的媒体数据的记录和管理，提供了一套设计实现网络视频监控系统中的文件系统的完整解决方案，并就其中的关键问题进行了探讨。     

MIJ2K Optimization using evolutionary multiobjective optimization algorithms

This paper deals with the multiobjective definition of video compression and its optimization. The optimization will be done using NSGA-II, a well-tested and highly accurate algorithm with a high convergence speed developed for solving multiobjective problems. Video compression is defined as a problem including two competing objectives. We try to find a set of optimal, so-called Pareto-optimal solutions, instead of a single optimal solution. The two competing objectives are quality and compression ratio maximization. The optimization will be achieved using a new patent pending codec, called MIJ2K, also outlined in this paper. Video will be compressed with the MIJ2K codec applied to some classical videos used for performance measurement, selected from the Xiph.org Foundation repository. The result of the optimization will be a set of near-optimal encoder parameters. We also present the convergence of NSGA-II with different encoder parameters and discuss the suitability of MOEAs as opposed to classical search-based techniques in this field.     

Video Streaming for Mobile Video Surveillance

Mobile video surveillance represents a new paradigm that encompasses, on the one side, ubiquitous video acquisition and, on the other side, ubiquitous video processing and viewing, addressing both computer-based and human-based surveillance. To this aim, systems must provide efficient video streaming with low latency and low frame skipping, even over limited bandwidth networks. This work presents MoSES (MObile Streaming for vidEo Surveillance), an effective system for mobile video surveillance for both PC and PDA clients; it relies over H.264/AVC video coding and GPRS/EDGE-GPRS network. Adaptive control algorithms are employed to achieve the best tradeoff between low latency and good video fluidity. MoSES provides a good-quality video streaming that is used as input to computer-based video surveillance applications for people segmentation and tracking. In this paper new and general-purpose methodologies for streaming performance evaluation are also proposed and used to compare MoSES with existing solutions in terms of different parameters (latency, image quality, video fluidity, and frame losses), as well as in terms of performance in people segmentation and tracking.      

基于TMDXEVM6446的网络视频监控系统

网络视频监控系统是集视频编解码和流媒体传输技术为一体的综合系统,提供了实时快捷的监控服务,近年来得到越来越广泛的应用。本文详细介绍了H.264/AVC视频编码新标准在TMDXEVM6446平台上的移植和优化,并完成了基于H.264编解码的网络视频监控系统完整的设计与实现。     

A flexible and scalable component-based system architecture for video surveillance as a service,running on infrastructure as a service

There are many proposals for moving traditional video surveillance systems into the cloud, commonly known as Video Surveillance as a Service (VSaaS). Most systems use Hadoop technology for storing video records and distributing video analysis tasks. However, Hadoop is more appropriate for video retrieval services than real time video analysis. Also, existing systems offer neither flexible deployment plans, nor are they capable of automatically minimizing the number of required servers (whether they are physical or virtual machines). Our proposal involves the design and implementation of a component-based VSaaS running on Infrastructure as a Service (IaaS). This paper focuses on the design concepts and component functions that provide solutions for the availability and scalability of VSaaS. Our system can easily scale from one server up to a more complex cluster to support the varying requirements of users. It accesses cloud services via Amazon EC2 for computing services and Amazon S3 API for object storage services, since they are supported by many cloud computing IaaS providers. We also present a components deployment that is suitable for any size and type of system, which combines both physical and virtual machines. Experiments show that the system performs well, and can tolerate difficult scenarios.     

基于千兆以太网的数字视频监控系统在地铁中的应用

本文主要介绍了实现地铁视频监控的几种方式，比较了相应的几种图像压缩和传输的优缺点，提出了适合于地铁应用的以千兆以太网作为传输途径的数字视频监控系统设计方案。     

A general framework for managing and processing live video data with privacy protection

Though a large body of existing work on video surveillance focuses on image and video processing techniques, few address the usability of such systems, and in particular privacy issues. This study fuses concepts from stream processing and content-based image retrieval to construct a privacy-preserving framework for rapid development and deployment of video surveillance applications. Privacy policies, instantiated to as privacy filters, may be applied both granularly and hierarchically. Privacy filters are granular as they are applicable to specific objects appearing in the video streams. They are hierarchal because they can be specified at specific objects in the framework (e.g., users, cameras) and are combined such that the disseminated video stream adheres to the most stringent aspect specified in the cascade of all privacy filters relevant to a video stream or query. To support this privacy framework, we extend our Live Video Database Model with an informatics-based approach to object recognition and tracking and add an intrinsic privacy model that provides a level of privacy protection not previously available for real-time streaming video data. The proposed framework also provides a formal approach to implement and enforce privacy policies that are verifiable, an important step towards privacy certification of video surveillance systems through a standardized privacy specification language.     

SVAS: Surveillance Video Analysis System

This paper introduces a Surveillance Video Analysis System, called SVAS, for surveillance domain, in which the semantic rules and the definition of event models can be learned or defined by the user for automatic detection and inference of complex video events. In the scope of SVAS, an event model method named Interval-Based Spatio-Temporal Model (IBSTM) is proposed. SVAS can learn action models and event models without any predefined threshold values and generates understandable and manageable IBSTM event models. Hybrid machine learning methods are proposed and used. A set of feature models named Threshold Model, which reflects the spatio-temporal motion analysis of an event, is kept as the first model. As the second model, Bag of Actions (BoA) model is used in order to reduce the search space in the detection phase. Markov Logic Network (MLN) model, which provides understandable and manageable logic predicates for users, is kept as the third model. SVAS has high performance event detection capability due to its interval-based hierarchical manner. It determines related candidate intervals for each main model of IBSTM and uses the related main model when needed rather than using all models as a whole. The main contribution of this study is to fill the semantic gap between humans and video computer systems such that, on the one hand it decreases human intervention through its learning capabilities, but on the other hand it also enables human intervention when necessary through its manageable event model method. The study achieves all of them in the most efficient way through its machine learning methods. The proposed system is applied to different event datasets from CAVIAR, BEHAVE and our synthetic datasets. The experimental results show that our approach improves the event recognition performance and precision as compared to the current state-of-the-art approaches.     

数字视频监控系统研究与实现

文章深入分析了数字视频监控系统中的关键技术,并给出一个基于MPEG-4和实时媒体传输技术的系统设计方案,能够满足视频监控系统的需求.在视频采集过程中采用双缓冲技术加速视频流的采集.     

Nonchronological video synopsis and indexing

The amount of captured video is growing with the increased numbers of video cameras, especially the increase of millions of surveillance cameras that operate 24 hours a day. Since video browsing and retrieval is time consuming, most captured video is never watched or examined. Video synopsis is an effective tool for browsing and indexing of such a video. It provides a short video representation, while preserving the essential activities of the original video. The activity in the video is condensed into a shorter period by simultaneously showing multiple activities, even when they originally occurred at different times. The synopsis video is also an index into the original video by pointing to the original time of each activity. Video Synopsis can be applied to create a synopsis of an endless video streams, as generated by webcams and by surveillance cameras. It can address queries like "Show in one minute the synopsis of this camera broadcast during the past day'. This process includes two major phases: (i) An online conversion of the endless video stream into a database of objects and activities (rather than frames). (ii) A response phase, generating the video synopsis as a response to the user's query.     

The evolution of video surveillance: an overview

Over the past 10 years, computer vision research has matured significantly. Although some of the core problems, such as object recognition and shape estimation are far from solved, many applications have made considerable progress. Video Surveillance is a thriving example of such an application. On the one hand, worldwide the number of cameras is expected to continue to grow exponentially and security budgets for governments, corporations and the private sector are increasing accordingly. On the other hand, technological advances in target detection, tracking, classification, and behavior analysis improve accuracy and reliability. Simple video surveillance systems that connect cameras via wireless video servers to Home PCs offer simple motion detection capabilities and are on sale at hardware and consumer electronics stores for under $300. The impact of these advances in video surveillance is pervasive. Progress is reported in technical and security publications, abilities are hyped and exaggerated by industry and media, benefits are glamorized and dangers dramatized in movies and politics. This exposure, in turn, enables the expansion of the vocabulary of video surveillance systems paving the way for more general automated video analysis.     

采用压缩传感的鲁棒的视频指纹方案

视频指纹技术在视频检索、识别、安全等领域有着广泛的应用,提出一种基于压缩传感理论的鲁棒性视频指纹方法,该方法采用压缩传感的稀疏性和安全性对提取的视频关键帧进行采样,再对采样矩阵分块与分类,提取能量值大的一些子块构成新的特征矩阵.对特征矩阵使用奇异值分解,对较大奇异值量化编码生成指纹.同时,也提出了高效的两步匹配方案,通过粗精两步搜索对视频进行检索,提高了视频搜索速度,实验结果表明,能准确检测视频片段,对通常的视频处理具有较强鲁棒性,满足视频检索的实时要求.     

数字视频监控系统研究与实现

文章深入分析了数字视频监控系统中的关键技术,并给出一个基于MPEG-4和实时媒体传输技术的系统设计方案,能够满足视频监控系统的需求。在视频采集过程中采用双缓冲技术加速视频流的采集。     

Multipath routing and rate-controlled video encoding in wireless video surveillance networks

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—to bring down the overall system cost and increase feasibility, scalability, and performance—is to propose a new architecture for a wireless video surveillance network, whose telecommunication infrastructure is based on a wireless mesh network, and where video sources are able to estimate network bandwidth and consequently control their output rate. Multipath routing is applied in such a way that at least part of the information arrives at its destination even if a wireless link is shielded (maliciously or not). A case study is considered to discuss the performance of the proposed architecture, analyzing a comparison between single-path and multipath approaches.     

An advanced video-based system for monitoring active volcanoes

Video surveillance systems are consolidated techniques for monitoring eruptive phenomena in volcanic areas. Along with these systems, which use standard video cameras, people working in this field sometimes make use of infrared cameras providing useful information about the thermal evolution of eruptions. Real-time analysis of the acquired frames is required, along with image storing, to analyze and classify the activity of volcanoes. Human effort and large storing capabilities are hence required to perform monitoring tasks.In this paper we present a new strategy aimed at improving the performance of video surveillance systems in terms of human-independent image processing and storing optimization. The proposed methodology is based on real-time thermo-graphic analysis of the area considered. The analysis is performed by processing images acquired with an IR camera and extracting information about meaningful volcanic events.Two software tools were developed. The first provides information about the activity being monitored and automatically adapts the image storing rate. The second tool automatically produces useful information about the eruptive activity encompassed by a selected frame sequence.The software developed includes a suitable user interface allowing for convenient management of the acquired images and easy access to information about the volcanic activity monitored.     

H.264在分层网络视频监控系统中的应用研究*

随着数字图像压缩技术的发展,数字监控系统的应用已经成熟,基于数字图像压缩技术的视频监控系统得到了广泛应用。而数字监控系统也随着图像压缩技术的发展在更新换代,H264是一种新近成熟的、高效的视频压缩标准,它有着比以往压缩标准压缩效率更高,更能适应网络的特点。在深入分析了H264视频压缩技术的基础上,设计和实现了一套实用的分层网络视频监控系统。