海量监控视频快速回放与检索技术

为解决海量监控视频的快速浏览和检索,介绍了一种基于目标索引的视频摘要和检索方法。该方法在光流分析的基础上,在画面的静止区域更新背景,运动的区域利用差分法分割出运动目标图像。经过优化的快速特征匹配和建立运动跟踪模型后,根据目标运动轨迹,按照时空距离进行聚类。在目标图像数据和运动参数进行XML结构化存储为索引的基础上,最后在检索时将符合条件的所有目标图像,按照其原有时间顺序逐帧贴到同一个背景图像中,形成动态的摘要视频。由于该方法剔除了背景中大量的时空冗余信息,可在较短回放时间内浏览全部有用目标,显著提高海量监控视频的查阅效率。     

基于运动目标的监控视频检索方法

随着我国视频监控网络的不断壮大,监控视频数据呈现海量增长的趋势,如何快速有效地进行监控视频检索变得越来越重要。提出一种基于运动目标的监控视频检索方法。对监控视频中的运动目标提取特征,生成相应的视频描述文件,通过匹配查询图片与描述文件中的运动目标特征最终找到相似对象出现的视频片断。实验表明,该方法实用性较好。     

视频中运动目标分类识别技术

随着科学技术的发展,计算机视频技术随之发展起来.基于视频中运动目标分类识别技术是计算机视频领域发展的一大重要突破点.视频中运动目标分类识别技术是将特定运动目标分为几种类别,然后对特定的类别进行识别跟踪.比如说马路上的视频监控系统,我们事先定义好特定的类别:人、汽车、自行车等等;而超市里面的视频监控系统,我们事先定义好特定的类别:人、食品、购物车等等.我们对不同的目标进行分类和总结.最后,根据各个目标的不同特征进行分类,通过分类后的特征进行识别,而满足我们对运动目标分类识别的要求.     

基于DSP的靶场远程视频监控系统的设计与实现

针对航天靶场的实际情况,设计了一种基于DSP的靶场远程视频监控系统;介绍了系统的总体硬软件结构,详细设计了系统的DSP视频处理模块、网络通信模块、视频接口模块,阐述了视频压缩包的格式和视频数据流的RTP封装方法,提出了一种对视频图像中运动目标的检测和提取算法;通过多次卫星发射任务检验,结果表明,该系统对运动目标的背景噪声具有明显的抑制作用,能够在复杂的图像背景下准确识别运动目标,并对其进行平稳跟踪;该系统对其它远程视频监控系统的设计具有一定的参考价值.     

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.     

AVE监控系统中基于轨迹约束的目标检索方法

针对增强虚拟环境(AVE)视频监控系统,提出了一种基于目标二维图像特征和三维空时特征并进行轨迹约束的运动车辆检索方法.二维检索中采用SURF特征匹配进行目标精确定位;三维检索中通过提取运动目标空时特征,充分利用AVE系统中摄像头关联信息进行关联分析,缩小目标搜索范围.实验结果表明,该算法具有较高的检索效率与精度,特别适用于多摄像头AVE监控系统中目标快速定位,掌握其在监控区域中的全空间运动信息.     

一种快速的视频跟踪算法

在摄像头固定的视频监控系统中,本文给出了一种基于最小化随机复杂度的快速有效的视频目标跟踪算法.该算法结合了基于背景减技术和目标相似性建模的优势,不需要调整参数权重.实验结果表明,应用本方法能快速的估计运动目标的位置和矩形轮廓.     

基于OpenCV的视频运动目标检测及其应用研究

高斯混合模型已经成为对视频利用背景减除法进行运动目标检测的最多的一种背景建模模型,也成为一种标准模型。首先对高斯混合模型的理论框架进行了分析,然后采用OpenCV技术实现高斯混合模型来检测视频运动目标,实验结果表明高斯混合模型对摄像头静止的道路监控视频运动目标检测具有较好的效果。最后以该运动目标检测技术为基础设计了一种智能视频监控系统,该系统具有较好的实用性。     

一种智能视频监控系统的设计与实现

针对现有的视频监控系统中对运动目标的检测不足,设计一种智能视频监控报警系统,DSP进行视频图像的捕获,预处理,监控,单片机控制视频数据的传输,存储和报警。     

运动目标跟踪研究

运动目标跟踪是智能视频监控系统的核心处理技术,是监控系统实现智能化的关键。跟踪过程中由于光线、遮挡等问题的存在,对相邻的视频序列中同一目标进行准确定位造成很大影响。主要对单摄像机内运动目标的稳定跟踪以及遮挡处理进行研究。     

Infrared single‐pixel video imaging for sea surface targets surveillance

This paper presents an infrared single‐pixel video imaging to surveille sea surface. Based on the temporal redundancy of the surveillance video, a two‐step scheme, including low‐scale detection and high‐scale detection, is proposed. For each frame, low‐scale detection performs low‐resolution single‐pixel imaging to obtain a “preview” image of the scene, where the moving target can be located. These targets are further refined in the high‐scale detection where the high‐resolution single‐pixel imagings focusing on these targets are used. The frame is reconstructed by merging these two‐level images. The simulated experiments show that for a video with 128 × 128 pixels and 150 frames, the sampling rate of our scheme is about 17.8%, and the reconstructed video presents a good visual quality.     

The Application of Video Semantics and Theme Representation in Automated Video Editing

This paper considers the automated generation of humorous video sequences from arbitrary video material. We present a simplified model of the editing process. We then outline our approach to narrativity and visual humour, discuss the problems of context and shot-order in video and consider influences on the editing process. We describe the role of themes and semantic fields in the generation of content oriented video scenes. We then present the architecture of AUTEUR, an experimental system that embodies mechanisms to interpret, manipulate and generate video. An example of a humorous video sequence generated by AUTEUR is described.     

VCMF: A Framework for Video Content Modeling

Current approaches to modeling the structure and semantics of video recordings restrict its reuse. This is because these approaches are either too rigidly structured or too generally structured and so do not represent the structural and semantic regularities of classes of video recordings. This paper proposes a framework which tackles the problem of reuse by supporting the definition of a wide range of models of video recordings and supporting reuse between them. Examples of the framework's use are presented and examined with respect to different kinds of reuse of video, current research, and the development of a toolset to support the framework.     

Model-Based Video Classification toward Hierarchical Representation,Indexing and Access

In this paper, we develop a content-based video classification approach to support semantic categorization, high-dimensional indexing and multi-level access. Our contributions are in four points: (a) We first present a hierarchical video database model that captures the structures and semantics of video contents in databases. One advantage of this hierarchical video database model is that it can provide a framework for automatic mapping from high-level concepts to low-level representative features. (b) We second propose a set of useful techniques for exploiting the basic units (e.g., shots or objects) to access the videos in database. (c) We third suggest a learning-based semantic classification technique to exploit the structures and semantics of video contents in database. (d) We further develop a cluster-based indexing structure to both speed-up query-by-example and organize databases for supporting more effective browsing. The applications of this proposed multi-level video database representation and indexing structures for MPEG-7 are also discussed.     

一种整体的视频匹配方法

给出一种视频时空配准的整体方法,提出一种视频内匹配与视频间匹配相结合的空间配准策略,改进动态时间扭曲方法以用于时间维的对齐.视频内匹配跟踪视频内各帧图像的特征点并记录其轨迹,视频间匹配配准不同视频的帧图像,使用轨迹对应提供图像配准所需的初始特征点对应,根据图像配准得到的特征点对应建立和更新轨迹对应.该匹配策略充分利用了视频的连贯性提高了匹配的稳定性和效率,同时提高了配准视频的连贯性.改进的动态时间扭曲方法通过极小化两段视频的整体距离建立视频之间的帧对应关系,保持视频内部各帧之间的时序关系并能处理非线性偏移     

Columbia's VoD and Multimedia Research Testbed with Heterogeneous Network Support

This paper reports our progress in developing an advanced video-on-demand (VoD) testbed, which will be used to accommodate various multimedia research and applications such as Electronic News on Demand, Columbia's Video Course Network, and Digital Libraries. The testbed supports delivery of MPEG-2 audio/video stored as transport streams over various types of networks, e.g., ATM, Ethernet, and wireless. Both software and hardware video encoders/decoders are used in the testbed. A real-time video pump and a distributed application control protocol (MPEG-2's DSM-CC) have been incorporated. Hardware decoders and set-tops are being used to test wide-area video interoperability. Our VoD testbed also provides an advanced platform for implementing proof-of-concept prototypes of related research. Our current research focus covers video transmission with heterogeneous quality-of-service (QoS) provision, variable bitrate (VBR) traffic modeling, VBR server scheduling, video over Internet, and video transmission over IP-ATM hybrid networks. An important aim is to enhance interoperability. Accommodation of practical multimedia applications and interoperability testing with external VoD systems has also been undertaken.     

Metadata-driven interactive web video assembly

The recent expansion of broadband Internet access led to an exponential increase of potential consumers of video on the Web. The huge success of video upload websites shows that the online world, with its virtually unlimited possibilities of active user participation, is an ideal complement to traditional consumption-only media like TV and DVD. It is evident that users are willing to interact with content-providing systems in order to get the content they desire. In parallel to these developments, innovative tools for producing interactive, non-linear audio-visual content are being created. They support the authoring process alongside management of media and metadata, enabling on-demand assembly of videos based on the consumer’s wishes. The quality of such a dynamic video remixing system mainly depends on the expressiveness of associated metadata. Eliminating the need for manual input as far as possible, we aim at designing a system which is able to automatically enrich its own media and metadata repositories continuously. Currently, video content remixing is available on the Web mostly in very basic forms. Most platforms offer upload and simple modification of content. Although several implementations exist, to the best of our knowledge no solution uses metadata to its full extent to dynamically render a video stream based on consumers’ wishes. With the research presented in this paper, we propose a novel concept to interactive video assembly on the Web. In this approach, consumers may describe the desired content using a set of domain-specific parameters. Based on the metadata the video clips are annotated with, the system chooses clips fitting the user criteria. They are aligned in an aesthetically pleasing manner while the user furthermore is able to interactively influence content selection during playback at any time. We use a practical example to clarify the concept and further outline what it takes to implement a suchlike system.

VisualGREP: A Systematic Method to Compare and Retrieve Video Sequences

Multimedia Tools and Applications - In this paper, we consider the problem of similarity between video sequences. Three basic questions are raised and (partially) answered. Firstly, at what...     

Detecting Roads in Stabilized Video with the Spatio-Temporal Structure Tensor

Video provides strong cues for automatic road extraction that are not available in static aerial images. In video from a static camera, or stabilized (or geo-referenced) aerial video data, motion patterns within a scene enable function attribution of scene regions. A “road”, for example, may be defined as a path of consistent motion — a definition which is valid in a large and diverse set of environments. The spatio-temporal structure tensor field is an ideal representation of the image derivative distribution at each pixel because it can be updated in real time as video is acquired. An eigen-decomposition of the structure tensor encodes both the local scene motion and the variability in the motion. Additionally, the structure tensor field can be factored into motion components, allowing explicit determination of traffic patterns in intersections. Example results of a real time system are shown for an urban scene with both well-traveled and infrequently traveled roads, indicating that both can be discovered simultaneously. The method is ideal in urban traffic scenes, which are the most difficult to analyze using static imagery.