Abstracting Digital Movies Automatically

Large video-on-demand databases consisting of thousands of digital movies are not easy to handle: the user must have an attractive means of retrieving his movie of choice. For analog video, movie trailers are produced to allow a quick preview and perhaps stimulate possible buyers. This paper presents techniques for automatically producing such movie abstracts of digital videos.     

Location based abstraction of user generated mobile videos

Demand for efficient ways to represent vast amount of video data has grown rapidly in recent years. The advances in positioning services have led to new possibilities in combining location information to video content. In this paper we present an automatic video editing system for geotagged mobile videos. In our solution the system creates automatically a video summary from a set of unedited video clips. Location information and timestamps are used to group video clips with the same context properties. The groups are used to create a video summary where subshots from same context group are represented as scenes. The novelty in our solution lies in combining geotags with low level content analysis tools in video abstraction. We have evaluated the created video summaries with a group of users and the system usability for service creation by building a semi-automatic web-based video editing service. The evaluations prove that our concept is useful as it improves coherence and enjoyability of the automatic video summaries.     

Video abstraction based on the visual attention model and online clustering

With the fast evolution of digital video, research and development of new technologies are greatly needed to lower the cost of video archiving, cataloging and indexing, as well as improve the efficiency and accessibility of stored video sequences. A number of methods to respectively meet these requirements have been researched and proposed. As one of the most important research topics, video abstraction helps to enable us to quickly browse a large video database and to achieve efficient content access and representation. In this paper, a video abstraction algorithm based on the visual attention model and online clustering is proposed. First, shot boundaries are detected and key frames in each shot are extracted so that consecutive key frames in a shot have the same distance. Second, the spatial saliency map indicating the saliency value of each region of the image is generated from each key frame and regions of interest (ROI) is extracted according to the saliency map. Third, key frames, as well as their corresponding saliency map, are passed to a specific filter, and several thresholds are used so that the key frames containing less information are discarded. Finally, key frames are clustered using an online clustering method based on the features in ROIs. Experimental results demonstrate the performance and effectiveness of the proposed video abstraction algorithm.     

On the use of hierarchical prediction structures for efficient summary generation of H.264/AVC bitstreams

Video summarization refers to an important set of abstraction techniques aimed to provide a compact representation of the video essential to effectively browse and retrieve video content from multimedia repositories. Most of these video summarization techniques, such as image storyboards, video skims and fast previews, are based on selecting some frames or segments. H.264/AVC has become a widely accepted coding standard and is expected that many of the content will be available in this format soon. This paper proposes a generic model of video summarization especially suitable for generating summaries of H.264/AVC bitstreams in a highly efficient manner, using the concept of temporal scalability via hierarchical prediction structures. Along with the model, specific examples of summarization techniques are given to prove the utility of the model.     

一种新的动态视频摘要生成方法

本文提出了一种概要序列形式的视频摘要生成方法.在视频结构化的基础上,从减少信息冗余和保持本质内容两个角度出发,分别定义了镜头(场景)的冗余度和语义重要度,据此推导出视频内容缩减和保持的原则;之后,综合可理解性的要求,给出了一种自上而下的视频摘要生成方法.以电影动作片为例的实验结果证实了方法的有效性.     

A New Learning Algorithm for the Fusion of Adaptive Audio–Visual Features for the Retrieval and Classification of Movie Clips

This paper presents a new learning algorithm for audiovisual fusion and demonstrates its application to video classification for film database. The proposed system utilized perceptual features for content characterization of movie clips. These features are extracted from different modalities and fused through a machine learning process. More specifically, in order to capture the spatio-temporal information, an adaptive video indexing is adopted to extract visual feature, and the statistical model based on Laplacian mixture are utilized to extract audio feature. These features are fused at the late fusion stage and input to a support vector machine (SVM) to learn semantic concepts from a given video database. Based on our experimental results, the proposed system implementing the SVM-based fusion technique achieves high classification accuracy when applied to a large volume database containing Hollywood movies.     

Fast data broadcasting and receiving scheme for popular videoservice

Using multiple channels to broadcast a popular video can reduce the viewer's waiting time to approach video-on-demand service. For a given bandwidth allocation, pyramid broadcasting schemes can provide users with shorter waiting time as compared with conventional broadcasting schemes. However, for a 120-minute movie, the waiting time is only reduced to 20 minutes as we allocate 4 video channels for the movie. The harmonic broadcasting scheme can reduce the waiting time to 4 minutes but it can not support the live telecast. This paper presents a new broadcasting scheme, which can support live videos and reduce the waiting time to 8 minutes for the above case. With the same waiting requirement for a hot video, the new scheme can greatly reduce the bandwidth requirements and provide heterogeneous users' services     

Statistical models of video structure for content analysis andcharacterization

Content structure plays an important role in the understanding of video. In this paper, we argue that knowledge about structure can be used both as a means to improve the performance of content analysis and to extract features that convey semantic information about the content. We introduce statistical models for two important components of this structure, shot duration and activity, and demonstrate the usefulness of these models with two practical applications. First, we develop a Bayesian formulation for the shot segmentation problem that is shown to extend the standard thresholding model in an adaptive and intuitive way, leading to improved segmentation accuracy. Second, by applying the transformation into the shot duration/activity feature space to a database of movie clips, we also illustrate how the Bayesian model captures semantic properties of the content. We suggest ways in which these properties can be used as a basis for intuitive content-based access to movie libraries.     

基于本体论的个性化影片推荐技术研究

个性化影片推荐服务是解决目前网络及家庭数字电视应用中影片资源迅速增长,用户"信息迷航"的有效方法.针对影片点播应用,给出了个性化影片推荐服务的体系结构、影片数据建模、用户兴趣偏好模型进行了研究,实现无需用户输入传统推荐方法所需相关个性兴趣信息即可返回与用户当前兴趣相关的影片推荐列表,提出了基于本体论的影片模型,并建立用户兴趣偏好模型,给出了对推荐过程中结合用户信息反馈对推荐结果进行自适应的调整算法.     

Scalable On-Demand Streaming of Nonlinear Media

A conventional video file contains a single temporally-ordered sequence of video frames. Clients requesting on-demand streaming of such a file receive (all or intervals of) the same content. For popular files that receive many requests during a file playback time, scalable streaming protocols based on multicast or broadcast have been devised. Such protocols require server and network bandwidth that grow much slower than linearly with the file request rate. This paper considers ldquononlinearrdquo video content in which there are parallel sequences of frames. Clients dynamically select which branch of the video they wish to follow, sufficiently ahead of each branch point so as to allow the video to be delivered without jitter. An example might be ldquochoose-your-own-endingrdquo movies. With traditional scalable delivery architectures such as movie theaters or TV broadcasting, such personalization of the delivered video content is very difficult or impossible. It becomes feasible, in principle at least, when the video is streamed to individual clients over a network. For on-demand streaming of nonlinear media, this paper analyzes the minimal server bandwidth requirements, and proposes and evaluates practical scalable delivery protocols.     

Adaptive fast data broadcasting scheme for video-on-demand service

As we support video-on-demand (VOD) service with batching schemes, the bandwidth requirement will be very large for a popular movie. For a hot video, fast data broadcasting scheme substantially reduce the bandwidth requirements as compared with batching schemes. However, the fast data broadcasting scheme needs to predict which movie is hot. If the prediction is not accurate, the allocated bandwidth will be wasted. This paper presents a new data broadcasting scheme for VOD service. For a movie, as it is popular, the new scheme will work like the fast data broadcasting scheme to save the communication bandwidth. If there is no request for the movie, the new scheme will not allocate bandwidth for the movie. Therefore, the bandwidth allocation for a movie is always efficient whether or not the movie is popular     

一种基于交互信息量的视频摘要生成方法

提出了一种基于交互信息量的视频摘要生成方法。该方法首先使用基于交互信息量的方法进行视频镜头检测,通过对检测到镜头帧的聚类提取镜头候选关键帧。然后对候选关键帧按照相邻帧间交互信息量的比较来提取镜头关键帧,最后将镜头关键帧按时序排列在一起形成视频摘要。试验表明,这种关键帧提取算法是有效的,其建立的视频摘要能较好的反映原视频的内容。     

IM(S)2: Interactive movie summarization system

The need of summarization methods and systems has become more and more crucial as the audio-visual material continues its critical growth. This paper presents a novel vision and a novel system for movies summarization. A video summary is an audio-visual document displaying the essential parts of an original document. However, the definition of the term “essential” is user-dependent. The advantage of this work, unlike the others, is the involvement of users in the summarization process. By means of IM(S)², people generate on the fly customized video summaries responding to their preferences. IM(S)² is made up of an offline part and an online part. In the offline, we segment the movies into shots and we compute features describing them. In the online part users inform about their preferences by selecting interesting shots. After that, the system will analyze the selected shots to bring out the user’s preferences. Finally the system will generate a summary from the whole movie which will provide more focus on the user’s preferences. To show the efficiency of IM(S)², it was tested on the database of the European project MUSCLE made up of five movies. We invited 10 users to evaluate the usability of our system by generating for every movie of the database a semi-supervised summary and to judge at the end its quality. Obtained results are encouraging and show the merits of our approach.     

机载高性能多格式视频叠加技术

随着计算机技术与视频图形图像技术的不断发展,机载航空电子系统中的综合显示处理技术也得以长足发展,需要处理和显示的视频信息量越来越大,格式越来越多。文章研究能够在机载综合显示系统中实现多种视频格式的选择和叠加功能。结合机载综合显示系统对视频技术的需求,研究了高性能多格式视频叠加模块的硬件设计和软件叠加算法。在机载综合显示系统液晶显示器上实现了叠加后的视频图像,满足了机载显示系统的要求。     

基于内容分发网络的视频通信系统研究

随着宽带技术和业务的发展以及人们对视频通信需求的增长,视频通信业务和技术得到了大规模的发展。首先比较了目前各种实现方案的特点和不足;然后基于内容分发网络技术及系统,提出了一种低成本、高扩展性、高质量视频通信的系统方案,详细叙述了该方案的结构、流程及特点;最后给出了验证系统的初步结果。     

图像处理技术在焊缝跟踪中的应用

随着焊接过程自动化和智能化的发展,基于图像处理技术的焊缝位置检测和焊接缺陷检测过程越来越受到国内外学者的重视。文章对焊缝自动跟踪系统中有关图像处理方面的研究现状作了一些介绍,详细分析了图像处理技术在焊缝跟踪过程中的应用,其中包括图像预处理、图像分割、边缘检测和特征点提取等图像处理过程,总结了一些传统和新型的图像处理算法,并讨论了各自的优缺点。     

变电站综合视频监控系统初探

随着电力系统改造和自动化建设不断发展完善,视频监控系统在变电站自动化系统中占有了越来越重要的地位,本文详细介绍了原有变电站视频监控系统的不足,着重对现有变电站视频监控及环境监控应用进行了需求分析,并就变电站综合视频监控系统探讨了相应的解决方案。     

A Resource Allocation Framework for Scalable Video Broadcast in Cellular Networks

Video streaming is one of the most important applications that will make use of the high data rates offered by 4G networks. The current video transport techniques are already very advanced, and the more immediate problems lie in the joint optimization of video coding, AL-FEC, and PHY rate selection with the goal of enhancing the user perceived quality. In this work we provide an analysis of video broadcast streaming services for different combinations of layered coding and AL-FEC, using a realistic LTE PHY layer. Our simulation results show that the scalable content adaptation given by Scalable Video Coding (SVC) and the scheduling flexibility offered by the 3G-LTE MAC-layer provide a good match for enhanced video broadcast services for next generation cellular networks. Our proposed solution is compared to baseline algorithms and broadcast systems based on H.264/AVC streaming solutions. We emphasize the system quality improvement brought by our solution and discuss implications for a wide-scale practical deployment.