基于视频推荐技术的无线网络视频服务器设计

无线网络视频服务器中视频推荐技术已成为重要技术之一,视频推荐技术是为了用户在使用无线网络是视频务器时,更快的找到感兴趣的视频;采用当前方法对用户进行视频推荐时,未考虑用户的兴趣偏好是否随着时间有所变化,使视频推荐出现偏差;为此,提出一种基于视频推荐技术的无线网络视频服务器设计方法;该方法首先使用无线网络视频服务器硬件部分的MPEG-4进行视频数据采集,并对MPEG-4采集的视频数据进行整理;在由软件部分把采集到的视频数据储存到缓冲区,进行视频缓冲,并建立视频数据队列进行视频数据输送;以计算无线网络视频的相似度来搜索相近视频,将搜索到的视频与目标用户观看过的视频进行对比,对比相似度越接近1,则说明用户对推荐视频感兴趣的几率大,反之越接近-1用户对推荐视频越不感兴趣;此计算方法能有效的从海量视频数据中快速的搜索出目标用户感兴趣视频;实验结果表明,将视频推荐技术应用到无线网络视频中可以迅速准确的搜索出目标用户感兴趣视频。     

一种面向动画视频的摘要方法

动画视频摘要是目前热门的动画视频处理和检索技术的重要组成部分.针对动画视频与新闻视频、体育运动视频显著不同的特点,提出了一种适合动画视频的摘要方法.首先通过对动画视频的结构分析得到动画视频的可视特征与层次结构,然后分析动画视频内容的重要度选取视频中的重要片段,最后通过缩略粒度选择,按照时序方式组合得到故事板和缩略视频形式的视频摘要.实验证明,该方法比较有效地获得了动画视频摘要,两种形式的摘要对动画视频能够很好的概括和缩略.     

嵌入式无线视频监控系统设计

本嵌入式无线视频监控系统采用高性能ARM9芯片作微处理器,通过嵌入式Linux采集USB摄像头视频数据,并将采集的视频数据帧经JPEG压缩;在ARM9芯片的控制下,通过2.4GHz无线发送/接收模块进行视频数据传输;无线接收端再将视频数据通过网络接口提交给视频应用服务端;最后由视频应用服务端将接收到的压缩数据帧重组、复合成视频图像,实现无线视频监控.     

基于动画特征的视频 方法*

针对动画视频与新闻视频、体育运动视频的不同特点,提出了一种适合动画视频的 技术。首先通过对动画视频的结构分析得到动画视频的可视特征与层次结构;然后根据动画视频内容的重要度来选取视频中的重要片段;最后通过粒度选择,按照时序方式组合得到故事板和缩略视频形式的视频 。实验表明该方法能有效地获得动画视频 。     

Windows视频驱动程序的技术剖析和比较

视频驱动程序是图像处理系统的基础环节,其效率、可靠性将直接影响图像处理系统的性能。文章论述了适合不同Windows操作系统的两种视频驱动程序的技术:适用于Win9x的基于虚拟环境的视频驱动程序技术和适用于Win2000/XP的基于WDM的视频驱动程序技术。并以开发BT878卡视频驱动程序为例,详细比较了两种视频驱动程序技术优缺点,基于WDM的视频驱动程序具有采集效率高、稳定性好、延时短和模块化程度高等许多优点,因此,基于WDM的视频驱动程序技术代表视频驱动程序技术发展的方向。     

新闻视频挖掘技术研究

新闻视频挖掘是一个新兴的研究领域,也是多媒体数据挖掘的典型代表。本文对新闻视频挖掘技术进行了全面深入的讨论,首先从概念上对新闻视频挖掘进行了界定,提出了新闻视频挖掘的层次框架和技术框架,指出新闻视频挖掘包括低层视频挖掘和高层视频挖掘两个层次。其中,低层视频挖掘是利用数据挖掘的方法对视频内容进行分析的过程,而高层数据挖掘则是在低层挖掘的基础上进一步发现视频中的知识的过程。新闻视频挖掘的技术框架则对挖掘所涉及到的具体技术进行了分析。最后,对新闻视频挖掘中的结构挖掘、语义内容挖掘、视频摘要、趋势挖掘、关联挖掘等任务进行了详细的阐述,并对各种任务举出了具体的示例加以说明。     

面向工业4.0的多维视频监控系统设计

针对多维视频监控受到图像噪声的影响,导致多维视频的质量变差,以提高多维视频图像的质量为目的,提出了面向工业4.0的多维视频监控系统设计;在第四次工业革命的背景下,利用多维视频采集器设计和监控网络传输接口设计,完成了系统的硬件设计;确定多维视频背景中的图片像素点,提取多维视频背景,通过低通滤波来阻止视频更新的影响,根据帧多维视频的检测结果来更新多维视频的背景,提出多维视频跟踪算法,完成了系统的软件设计,实现了多维视频的监控;测试结果表明,与其他两个多维视频监控系统相比,面向工业4.0的多维视频监控系统可以将噪声消除掉80%~90%,平均压缩比为80.004:1,平均分辨率大约为533*533 dpi,可以获得较高质量的多维视频图像。     

Finding a needle in a haystack: an interactive video archive explorer for professional video searchers

Professional video searchers typically have to search for particular video fragments in a vast video archive that contains many hours of video data. Without having the right video archive exploration tools, this is a difficult and time consuming task that induces hours of video skimming. We propose the video archive explorer, a video exploration tool that provides visual representations of automatically detected concepts to facilitate individual and collaborative video search tasks. This video archive explorer is developed by employing a user-centred methodology, which ensures that the tool is more likely to fit to the end user needs. A qualitative evaluation with professional video searchers shows that the combination of automatic video indexing, interactive visualisations and user-centred design can result in an increased usability, user satisfaction and productivity.     

3D-List: a data structure for efficient video query processing

A video query model based on the content of video and iconic indexing is proposed. We extend the notion of two-dimensional strings to three-dimensional strings (3D-Strings) for representing the spatial and temporal relationships among the symbols in both a video and a video query. The problem of video query processing is then transformed into a problem of three-dimensional pattern matching. To efficiently match the 3D-Strings, a data structure, called 3D-List, and its related algorithms are proposed. In this approach, the symbols of a video in the video database are retrieved from the video index and organized as a 3D-List according to the 3D-String of the video query. The related algorithms are then applied on the 3D-List to determine whether this video is an answer to the video query. Based on this approach, we have started a project called Vega. In this project, we have implemented a user friendly interface for specifying video queries, a video index tool for constructing the video index, and a video query processor based on the notion of 3D-List. Some experiments are also performed to show the efficiency and effectiveness of the proposed algorithms     

立体视频点播系统设计与实现

立体视频是今年来视频处理领域的研究热点,是未来视频技术的发展方向。本文介绍了立体视频点播系统的结构框架,简要介绍了H.264视频编码标准,给出了基于H.264的立体视频编码方案,设计了立体视频的传输方案,最后实现了一个基于简单网络环境下的立体视频点播系统。     

AVCon视频会议的研究与实现

介绍了AVcon视频产品的一些关键技术（视频压缩、视频传输、视频编解码）以及基于H．323标准的全面视频网络实现厦应用。     

Example-based video remixing

A video remix is generally created by arranging selected video clips and combining them with other media streams such as audio clips and video transition effects. This paper proposes a system for semi-automatically creating video remixes of good expressive quality. Given multiple original video clips, audio clips, and transition effects as the input, the proposed system generates a video remix by five processes: I) video clip sequence generation, II) audio clip selection, III) audio boundary extraction, IV) video segment extraction, and V) transition effect selection, based on the spatial and temporal structural patterns automatically learned from professionally created video remix examples. Experiments using movie trailers of action genre as video remix examples not only demonstrate that video remixing by professionals can be imitated based on examples but also reveal that the video clip sequence generation and audio clip selection are the most important processes to improve the perceived expressive quality of video remixes.     

鲁棒视频水印研究进展

数字视频在当前通信世界中被认为是一种重要而有效的媒体,广泛应用于新闻、短视频和有线网络广播视频节目中。随着计算机与互联网技术的发展,数字视频内容容易被侵权使用者肆意复制和传播,如何保护视频版权日益成为人们关注的问题。鲁棒视频水印是实现视频版权保护的一种有效手段。作为数字视频水印的分支,鲁棒视频水印是一种通过特定算法在需要被保护的视频对象中嵌入秘密信息——水印来证明版权归属的技术。本文对当前的视频水印技术进行了概述,对视频水印的概念、应用场景、分类方式、设计要求、发展历程和相关经典方法进行了介绍和梳理。本文归纳总结了2016—2021年鲁棒视频水印相关研究工作,包括基于内容的、基于码流的、基于深度学习和其他类型视频水印,并对其中部分工作进行了相应的性能比较和分析。其中,基于内容的视频水印方法将视频看做帧序列,由于在每一帧上应用水印算法,不考虑视频的编解码过程,这类方法实现简单,计算效率高;基于码流的视频水印方法将水印嵌入到编码比特流中,该方案更快速,故可支持实时视频水印应用;基于深度学习的方法取代了依靠手工设计的特征来提高水印的性能。最后分析了鲁棒视频水印的未来发展趋势。     

ClassView: hierarchical video shot classification, indexing, and accessing

Recent advances in digital video compression and networks have made video more accessible than ever. However, the existing content-based video retrieval systems still suffer from the following problems. 1) Semantics-sensitive video classification problem because of the semantic gap between low-level visual features and high-level semantic visual concepts; 2) Integrated video access problem because of the lack of efficient video database indexing, automatic video annotation, and concept-oriented summary organization techniques. In this paper, we have proposed a novel framework, called ClassView, to make some advances toward more efficient video database indexing and access. 1) A hierarchical semantics-sensitive video classifier is proposed to shorten the semantic gap. The hierarchical tree structure of the semantics-sensitive video classifier is derived from the domain-dependent concept hierarchy of video contents in a database. Relevance analysis is used for selecting the discriminating visual features with suitable importances. The Expectation-Maximization (EM) algorithm is also used to determine the classification rule for each visual concept node in the classifier. 2) A hierarchical video database indexing and summary presentation technique is proposed to support more effective video access over a large-scale database. The hierarchical tree structure of our video database indexing scheme is determined by the domain-dependent concept hierarchy which is also used for video classification. The presentation of visual summary is also integrated with the inherent hierarchical video database indexing tree structure. Integrating video access with efficient database indexing tree structure has provided great opportunity for supporting more powerful video search engines.     

InsightVideo: toward hierarchical video content organization for efficient browsing, summarization and retrieval

Hierarchical video browsing and feature-based video retrieval are two standard methods for accessing video content. Very little research, however, has addressed the benefits of integrating these two methods for more effective and efficient video content access. In this paper, we introduce InsightVideo, a video analysis and retrieval system, which joins video content hierarchy, hierarchical browsing and retrieval for efficient video access. We propose several video processing techniques to organize the content hierarchy of the video. We first apply a camera motion classification and key-frame extraction strategy that operates in the compressed domain to extract video features. Then, shot grouping, scene detection and pairwise scene clustering strategies are applied to construct the video content hierarchy. We introduce a video similarity evaluation scheme at different levels (key-frame, shot, group, scene, and video.) By integrating the video content hierarchy and the video similarity evaluation scheme, hierarchical video browsing and retrieval are seamlessly integrated for efficient content access. We construct a progressive video retrieval scheme to refine user queries through the interactions of browsing and retrieval. Experimental results and comparisons of camera motion classification, key-frame extraction, scene detection, and video retrieval are presented to validate the effectiveness and efficiency of the proposed algorithms and the performance of the system.     

视频数据的时间序列挖掘方法研究

不同类型的视频具有不同的内容和不同的内容组织结构.目前由于安全防护问题的升温,综合视频监控系统和交通监控系统引起了较多的关注.但是并没有文献对这一类型视频数据的挖掘提出一个较完整的挖掘框架.文中针对监控视频等具有相对固定背景特征视频数据的视频运动挖掘问题,提出了在跟踪视频对象运动的基础上,提取视频对象的运动轨迹,结合时间特性形成时间序列数据,并进一步对视频数据进行相似性查询和聚类挖掘的系统模型.     

基于SIP协议的网络视频监控系统的设计与实现

如何建立远程网络视频连接、实现NAT穿透并进行高效的视频流编解码是视频监控系统的研究难点,基于SIP协议建立的网络视频监控系统采用高压缩比的MEPG4视频编码格式,支持IP视频多路并发,利用软交换平台对视频流进行集中管理,实现了网络视频连接建立,视频流编解码、加密、传输,以及智能报警、录像、抓拍、回放等功能。     

视频结构挖掘的概念和框架

视频信息处理的关键是视频信息的结构化，视频除了有基本层次结构之外，还有隐藏其中的视频结构语法和结构语义。该文提出了一种视频结构挖掘的概念框架和视频结构挖掘的系统框架，在概念框架中对视频结构挖掘相关概念给出了明确定义和界定；视频结构挖掘框架主要包括：视频基本层次结构挖掘，视频结构语法挖掘和视频结构语义挖掘。讨论了视频结构模式和知识的具体应用，包括指导视频的组织与管理、实现基于内容的个性视频推荐和改善视频摘要系统。     

利用等价关系理论进行视频片段检索的方法

视频片段检索是基于内容的视频检索的主要方式,可是现有的片段检索方法大多只是对预先分割好的片段进行检索。为了从连续的视频节目中自动分割出多个相似的片段,提出了一种新的有效的视频片段检索方法,并首次尝试将等价关系理论应用于视频片段的检索.该方法首先用等价关系理论定义了片段匹配函数,同时采用滑动镜头窗自动分割出多个真正相似的片段;然后把等价类映射为矩阵表达形式,再通过矩阵的特性来度量影响片段相似度的不同因子,实现了相似片段的排序。实验结果表明,该方法能够一次性快速准确地从连续视频库中自动分割出与查询片段相似的多个片段。