基于DaVinci技术的嵌入式视频监控系统设计

针对视频监控系统实时性要求高运算量大的特点,提出了基于DaVinci技术的嵌入式视频监控系统设计方案.方案利用基于DaVinci技术的TMS320DM6467 ARM+DSP双核处理器,提高了系统性能,缩短了开发周期.ARM核植入嵌入式Web服务器,以UDP协议实时传输视频数据,实现控制模块与监控终端之间的通信.DSP内核视频数据编码算法选用H.264,大大提高了数据编码效率.     

基于软交换的视频监控系统设计

在比较目前各种视频监控系统技术优点的基础上,设计了基于软交换网络的视频监控系统。系统基于VOCAL协议栈设计开发了包括视频监控前端、视频监控用户终端、视频传输方案的整体方案。实现了标准软交换控制器与视频监控用户终端、视频监控前端之间的SIP通信和视频传输。并基于标准软交换服务器实现和验证了该设计方案。使视频监控系统能够在网络融合的大背景下,实现监控业务的融合。     

基于单片DSP的MPEG-4视频监控终端的实现

介绍了基于ADI公司的单片Blackfin DSP的视频监控终端的硬件、软件的设计和实现。该视频监控终端能够对CIF格式的PAL制视频信号按MPEG-4@L3标准进行实时编码,并具有网络通信的功能。     

基于双核DSP的嵌入式视频监控终端

随着市场对监控终端产品的需求越来越大,越来越多的人开始关注这个新兴产业,基于此,介绍了一种自行研究开发的基于Blackfin561双核DSP的嵌入式视频监控终端硬件结构,详细描述了终端系统各个软件功能模块的实现原理和技术,并结合实际测试出现的传输性能的问题进行了详细的分析和研究,得出影响系统视频传输性能的制约因素是PPPoE程序的性能,然后结合该嵌入式视频监控终端,对PPPoE的实现原理进行了研究,最后给出了两种PPPoE传输性能优化方案.     

基于DSP的脱机远程视频监控终端

介绍一个基于DSP的脱机远程视频监控终端的设计和实现，该系统采用CPLD完成图像采集的控制逻辑，以ADSP-21535为中央处理器完成图像MPEG4编码、编码数据网络传输平和本地存储。介绍监控终端的系统结构与流程，以及图像采集模块和网络接口模块的软硬件设计与实现，给出了系统的性能指标。     

基于DSP平台的网络视频监控系统构建

本文设计实现了一个基于DSP的嵌入式智能网络视频监控系统.整个系统包括视频服务器端、视频客户端和视频控制端三大部分.其中服务器端采用自行研制的嵌入式DSP开发平台实现,具有体积小、智能判断运动目标等特点.测试结果表明,该系统运行稳定,对于D1格式的视频图像,能达到实时网络视频监控的目的.     

基于GPRS的远程视频监控系统设计与实现

设计与实现了一个基于嵌入式平台和CPRS通信技术的无线远程视频监控系统,论述系统的总体结构及设计思路,并对视频采集和数据传输过程进行了详细分析.完成视频监控终端的软硬件设计,使监控终端通过无线网络和监控中心连接,通过实验实现可靠的无线数据传输.该方案具有成本低、体积小、易于安装等优点,具有广阔的应用前景.     

基于商密算法的视频终端安全接入系统的研究与实现

在电网视频监控系统不断发展的同时,视频终端接入监控系统时的安全问题也在不断突出,信息泄漏、数据篡改以及恶意攻击等问题严重威胁着电网的安全。本文基于电网视频监控系统的应用现状以及安全风险,结合电力安全防护的要求,设计一种基于商密算法的视频终端安全接入系统,可实现电力视频终端的安全接入。最后通过实验测试分析并验证了该系统能够满足电力视频监控的安全防护要求。     

基于Xscale和多DSP的智能视频监控系统的设计与实现

设计了基于PXA270Xscale处理器和多片TMS320DM642DSP处理器的并行智能视频监控系统,详细介绍了其体系结构的特点,关键模块的硬件组成及工作原理,并通过在该系统上实现运动目标的实时跟踪算法验证了系统的设计性能.验证结果表明,该监控系统具有处理速度快、接口丰富、成本低廉、可重构的特点,适合应用于视觉导航、安全监控等要求高速视频图像处理的场合.     

基于DSP的视频监控平台的设计

随着视频监控的不断发展和DSP技术的进步,基于DSP的视频监控受到越来越广泛的关注和应用.基于TI公司的TMS320DM6437设计了实时的网络视频监控平台.介绍了整个系统的框架,并对基于DSP/BIOS的软件设计进行了详细分析,如视频驱动、Codec Engine软件框架和网络传输.该平台具有视频信号采集、视频处理和视频传输的功能,可应用于不同的领域.     

GIS在智能交通系统交叉口监控中的应用研究

研究了智能交通系统中城市道路交叉口监控问题.着重针对交叉口监控中数据量大,且无法及时进行分析,动态调度和实时控制的问题进行了调查.通过对交叉口监控中大量数据的分析和整合,提出了利用地理信息系统和数据库有效解决海量数据存储和分析的方法.首先讨论了基于海量数据库的地理信息系统的技术框架,提出了一种基于Intergraph Geo-Media的交叉口交通监测模型以及系统实现方法,提高交通管理效率和城市道路利用率,接着探讨了基于GIS的智能交通交叉口监控系统亟需解决的问题.     

基于数据的分布式网络视觉监控系统设计与实现

数据的组成结构和存储管理方法是影响软件的运行效率和安全性、维护和扩展性以及通用性优劣的关键因素。本文介绍的分布式网络视觉监控系统是在分析归纳视觉监控系统数据的种类和操作处理特点的前提下,确定了分布式存储和管理数据的基础上所开发的软件。该系统在确保运行安全性的前提下较好地解决了监控系统处理数据量大、实时性要求高和网络运行效率的矛盾,同时软件的三层结构保证了系统组成配置的灵活性和通用性。     

自然保护区海量视频数据快速分析与检索

近年来,随着视频监控系统在自然保护区的大量部署,如何有效利用日益增加的海量视频监控数据成为亟待解决的难题.通过基于图像相似度的关键帧提取算法对海量视频数据进行清洗和压缩,同时利用基于深度学习的目标检测算法提取关键帧中的有效视频信息,并提供多种基于内容的视频检索方式,自动对用户提交的检索内容进行分析与处理,从而快速检索出感兴趣的视频.通过对青海湖野生动物视频监控数据进行分析与检索,验证了该系统的有效性.     

Automated Testing of Physical Security: Red Teaming Through Machine Learning

Modern surveillance systems for practical applications with diverse and mobile sensors are large, complex, and expensive. It is known that unexpected behaviors can emerge from such systems, and when these behaviors correspond to weaknesses in a surveillance system, we call them emergent vulnerabilities. Given their cost and importance to security, it is essential to test these systems for such vulnerabilities prior to deployment. To that end, we automate the testing process with multiagent systems and machine learning. However, the conventional—and most intuitive–approach is to focus the machine learning on the subject system, which leads to a high‐dimensional problem that is intractable. Instead, we demonstrate in this paper that learning attacks on the system is tractable and provides a viable testing method. We demonstrate this with a series of studies in simulation and with a small‐scale model system featuring elements typically found in real physical surveillance systems. Our machine learning method finds successful attacks in simulation, which we can duplicate with the physical system. The method is scalable, with the implication that it could be used to test larger, real surveillance installations.     

IP网络中高可靠性视频监控的组播设计

视频监控做为安全防范的一个重要手段已应用于各行各业,随着对视频监控的需求不断增加,传统的模拟视频监控技术已不能满足于人们对于图像质量高清、部署灵活、传输占用带宽小等应用的需求,逐渐转向基于IP承载网络的数字监控技术。那么如何使视频监控在IP网络中传输更稳定、可靠?本文将着重阐述如何基于组播技术规划、设计IP网络以满足在大型网络中视频监控的需求。     

A multi-agent architecture for supporting distributed normality-based intelligent surveillance

Intelligent surveillance involves the use of AI techniques to monitor environments whose analysis is becoming more and more complex because of the large number of sensors used and the need of monitoring multiple events of interest simultaneously. Most of the current surveillance systems provide solutions for particular problems but still suffer from lack of flexibility and scalability when they are used on different or related surveillance problems. To overcome this limitation, two aspects should be addressed: a knowledge-based surveillance model flexible enough to deal with different events of interest and an architecture that gives support to this model when deploying the surveillance system within a particular scenario. This paper discusses the architecture devised to deploy intelligent surveillance systems by means of a set of autonomous agents that are responsible for the management of different surveillance tasks and for cooperating to monitor complex environments. This multi-agent architecture is inspired by a normality-based formal model used to define the knowledge needed to analyze general-purpose surveillance concepts. We use the architecture to deploy a surveillance system to monitor an urban traffic scenario.     

Automated and coupled services of advanced smart surveillance systems toward green IT: tracking,retrieval and digital evidence

Green Security is a new research field defining and investigating security solutions using an energy-aware perspective. Growing efforts and interests for an intelligent or smart surveillance system which is capable of automatically detecting and tracking target objects is in the spotlight in the security community. So far, these technologies are mainly aimed at single camera applications and are evolving with the demand for wide-area surveillance systems currently. However, the tracking techniques used on a single camera have limitations in providing effective crime prevention and countermeasures when an incident occurs since an object is not linked to other cameras. In addition, the use of multi-camera systems for wide-area surveillance not only produces large amounts of video data to be stored, but also have more technical requirements in the interrelation between cameras or server. It require a considerable amount of time, manpower and energy in multi-camera tracking and back-tracking of objects. Therefore, we propose the advanced smart surveillance system for wide-areas which is capable of the automated tracking and retrieval of target object and digital evidence-video collection. Furthermore, we considered the multiple-camera environment with non-overlapping views which includes more constraint conditions by various light changes. This system enables real-time object tracking, fast post-retrieval and selective digital evidence collection with economy of time, manpower, memory devices, and energy consumption. Also, this system is more energy-efficient since our schemes are organically connected to each other.     

Intelligent video surveillance system: 3-tier context-aware surveillance system with metadata

This paper presents an intelligent video surveillance system with the metadata rule for the exchange of analyzed information. We define the metadata rule for the exchange of analyzed information between intelligent video surveillance systems that automatically analyzes video data acquired from cameras. The metadata rule is to effectively index very large video surveillance databases and to unify searches and management between distributed or heterogeneous surveillance systems more efficiently. The system consists of low-level context-aware, high-level context-aware and intelligent services to generate metadata for the surveillance systems. Various contexts are acquired from physical sensors in monitoring areas for the low-level context-aware system. The situation is recognized in the high-level context-aware system by analyzing the context data collected in the low-level system. The system provides intelligent services to track moving objects in Fields Of View (FOVs) and to recognize human activities. Furthermore, the system supports real-time moving objects tracking with Panning, Tilting and Zooming (PTZ) cameras in overlapping and non-overlapping FOVs.     

无线传感器监测网络分布式节点调度策略

无线传感器监测网络(WSSN)由数量众多的节点组成.每个节点通过传感器监测外界环境的变化并将监测数据以无线多跳的方式发回基站,实现对用户感兴趣的区域进行监测.WSSN节点的主要特点是电能、带宽、计算和存储能力等高度受限,尤其是其电源的不可替换性导致在保证对监测目标完全监测的同时延长系统工作寿命成为WSSN应用的一个中心问题.提出了WSSN的扩展工作寿命的定义,并在此基础上提出了一种延长WSSN工作寿命的分布式节点调度策略,在各节点簇内对节点进行调度以实现有差别监测服务并延长系统的工作寿命.提出的策略综合考虑节点的当前状态,具有较强的容错性.仿真实验结果表明相对于已提出的方法,该策略有效延长了WSSN的工作寿命.     

智能视觉监控技术研究进展

新一代智能视觉监控技术的研究是一个极具挑战性的前沿课题,它旨在赋予监控系统观察分析场景内容的能力,实现监控的自动化和智能化,因而具有巨大的应用潜力。视觉监控系统的智能化分析过程由运动目标检测、分类、跟踪和视频内容分析等几个基本环节组成,其中视频内容分析又包括异常检测、人的身份识别以及视频内容理解描述等。本文在总结以上有关关键技术研究进展的基础上,进一步提出将超分辨率复原技术引入视觉监控领域,介绍了超分辨率复原的主要算法及其在智能视觉监控中的应用。