融合视觉内容分析的网络视频缩略图推荐

视频在网站上呈现时,最先映入眼帘的都是一幅静态的封面图像——视频缩略图。主题明确且图像易见的视频缩略图,能让用户在预览时更容易、更快捷地抓住视频主题信息,提高该视频的吸引力,获得更多的点击量和提升用户的浏览体验及观看兴趣。本文针对网络视频缩略图的推荐,在视觉内容分析基础上,通过融合图像易获取性评价和视频内容代表性评价来获得缩略图推荐结果。在网络视频数据集上实施的主客观评价实验表明,本文方法所推荐的视频缩略图与原有人工标注的缩略图相比,有着较好的一致性,能够满足实际应用的需求。     

可用性增强的缩略图保持加密

传统加密在保护云储存图像隐私的同时使其完全丧失视觉可用性。尽管缩略图保持加密可平衡图像隐私性和视觉可用性，但现有方案均不考虑保留非视觉可用性。为此，提出一个可用性增强的缩略图保持加密方案。该方案利用信息隐藏的可逆性和灵活性，腾出原始图像的部分空间用于像素调整，从而保持密文缩略图与原始缩略图近似。在进行像素调整之前，对图像进行传统加密以保障安全性。在完成像素调整之后，凭借所剩余的空间容量嵌入额外信息，这些额外信息可为用户提供非视觉可用性。所提缩略图保持加密方案不仅平衡了隐私性和视觉可用性，还在一定程度上保留了非视觉可用性。最后，实验结果证实了所提方案的有效性和先进性。     

音乐可视化及其研究进展

随着计算机技术的发展,音乐的形象化出现了新的手段,这就是音乐可视化技术.作为听觉艺术与视觉艺术的结合体,音乐可视化已经得到了广泛关注.文章介绍了音乐可视化的概念与研究内容,从可视化音乐模型、可视化视觉模型、可视化系统、可视化的交互性四个层次着重分析和评述了目前国内外音乐可视化技术的研究进展,并分析了当前亟待解决的问题,展望了其未来的发展趋势.音乐可视化作为一种新型的可视化技术,仍存在许多问题需要解决,其研究具有很强的理论意义和实用价值.     

基于内容的多媒体数据查询和检索

多媒体数据具有可表现的视觉和听觉特性，而难于用符号形式来描述。本文介绍基于内容的对多媒体数据进行查询和检索的概念和方法，描述查询和检索的一般系统结构、用户查询类型、索引／过滤机制，以及视频的检索和浏览，并给出基于内容检索研究中值得探索的几个主要问题。     

一种启发式的用哼唱检索音乐的层次化方法

“用哼唱检索音乐”是一种友好的基于内容的音乐检索方法，它已经引起了广泛的研究兴趣；在对音乐库做了统计分析的基础上，总结了一些启发式规则，帮助对哼唱输入进行基音检测、音符分割，哼唱输入表达为音高轮廓图和节奏，音乐库中的音乐按音乐的节奏类型分为不同的节奏区域，并从每首音乐中抽取旋律轮廓图和节奏信息，用递归神经网络记忆旋律轮廓，音乐库的索引是神经网络的权值矩阵，将哼唱输入与音乐库中的音乐匹配的过程就是计算神经网络的输出过程。实验结果显示了所提方法的有效性。     

VRML可视化编辑器的研究与开发

对虚拟现实建模语言VRML可视化编辑器进行了研究,设计并实现了VRML可视化编辑器VisualVRMLEditor.构造了一个节点树视图,描述VRML文件的内部数据结构;构造了一个三维场景视图,显示了VRML文件所描述的三维场景;构造了一个路由视图,将路由这种无形的机制进行可视化编辑.实现了将节点树视图和三维场景视图结合起来,方便用户操作.此外,将路由这种无形的信息可视化,使用户能够进行可视化编辑路由,不用记住繁琐的VRML语法规则,提高了编辑VRML文件的效率.     

基于信息可视化的人机交互技术在视觉传达设计中的应用

信息可视化是一种将复杂的数据转化为可视化形式以便人们理解的技术。在人机交互领域,信息可视化技术被广泛应用于各种领域,随着互联网的发展,网络传输故障成为一个常见的问题。传统的网络故障监测方法存在效率低下且容易出现漏检情况。为解决此问题,研究首先通过图像处理技术提取视觉传达网络传输故障信息的特征量,并进行图像化处理分类;然后将图像化信息输入到分类器对故障信息进行分类和识别,最后将图像分类结果和人机交互技术相结合作为故障监测系统。结果表明研究构建的故障监测系统的故障监测准确率平均值为85.29%,误报率平均值为11.59%,同时在监测过程中的运行成本平均值为4 135.83元,所有结果均优于对比方法。这验证了研究提出的方法能提高视觉传达网络传输故障监测的精度,有较高的实用价值。     

基于Unity3D的虚拟博物馆信息可视化系统

信息可视化技术可以帮助我们加深对大规模复杂数据和信息间相互关系的理解, 而三维技术为信息可视化领域带来了新思路. 本文根据杭州工艺美术博物馆虚拟博物馆三维展厅浏览和藏品知识点信息浏览的可视化需求, 设计并实现了藏品信息可视化系统. 该系统基于Unity3D开发平台搭建, 根据杭州工艺美术博物馆虚拟博物馆藏品信息可视化需求分别设计实现相应的三维可视化组件, 通过Web3D客户端技术实现了用户通过浏览器高速、便捷地浏览博物馆三维可视化信息的功能需求.     

面向推荐系统的音乐特征抽取

音乐推荐系统是指根据用户的历史浏览数据,从候选库中推荐给用户可能喜欢的音乐的一种新型网络服务。该系统的关键在于需要对整个数据库按照音乐风格进行分类,基于此提出一种新的音乐特征处理方法来完成音乐库分类,以有效实现音乐推荐。该方法首先为候选音乐库构建常规的音乐特征数据集,然后基于分形理论对数据集进行属性约简,获取每一首音乐的推荐特征向量,并且依据特征向量的特点,定义了一种新的距离度量方法。在包含六种风格的音乐数据库的实验中,仿真结果证明了提出的音乐推荐特征和距离度量的有效性,与现有的基于内容的音乐检索研究相比,音乐推荐特征的使用极大地降低了对数据库存储量的需求,对音乐推荐系统的网络开发具有很好的应用价值。     

机载SAR实时成像系统中的数据可视化研究

SAR实时成像系统在国防等很多领域都有着重要的应用,系统对数据可视化方面的要求也越来越高,但目前国内对SAR实时成像系统的数据可视化方面的研究还不多,提出了一种针对SAR实时成像系统的新的数据可视化方案,并已在实际的飞行成像中得到了检验,新方案实时提供的信息更全面、更直观、可分析性更强,具有较强的信息表现能力和双向实时交互能力,能够较好地辅助对图像的在线分析,还对方案的重要组成部分－缩略图的原理和实现算法做了概括介绍。     

Visualization and User-Modeling for Browsing Personal Photo Libraries

We present a user-centric system for visualization and layout for content-based image retrieval. Image features (visual and/or semantic) are used to display retrievals as thumbnails in a 2-D spatial layout or “configuration” which conveys all pair-wise mutual similarities. A graphical optimization technique is used to provide maximally uncluttered and informative layouts. Moreover, a novel subspace feature weighting technique can be used to modify 2-D layouts in a variety of context-dependent ways. An efficient computational technique for subspace weighting and re-estimation leads to a simple user-modeling framework whereby the system can learn to display query results based on layout examples (or relevance feedback) provided by the user. The resulting retrieval, browsing and visualization can adapt to the user's (time-varying) notions of content, context and preferences in style and interactive navigation. Monte Carlo simulations with machine-generated layouts as well as pilot user studies have demonstrated the ability of this framework to model or “mimic” users, by automatically generating layouts according to their preferences.     

Multimedia Clip Generation From Documents for Browsing on Mobile Devices

Small displays on mobile handheld devices, such as personal digital assistants (PDAs) and cellular phones, are the bottlenecks for usability of most content browsing applications. Generally, conventional content such as documents and Web pages need to be modified for effective presentation on mobile devices. This paper proposes a novel visualization for documents, called multimedia thumbnails, which consists of text and image content converted into playable multimedia clips. A multimedia thumbnail utilizes visual and audio channels of small portable devices as well as both spatial and time dimensions to communicate text and image information of a single document. The proposed algorithm for generating multimedia thumbnails includes 1) a semantic document analysis step, where salient content from a source document is extracted; 2) an optimization step, where a subset of this extracted content is selected based on time, display, and application constraints; and 3) a composition step, where the selected visual and audible document content is combined into a multimedia thumbnail. Scalability of MMNails that allows generation of multimedia clips of various lengths is also described. A user study is presented that evaluates the effectiveness of the proposed multimedia thumbnail visualization.     

Human motion capture data retrieval based on semantic thumbnail

We present a method for the efficient retrieval and browsing of immense amounts of realistic 3D human body motion capture data. The proposed method organizes motion capture data based on statistical K-means (SK–means), democratic decision making, unsupervised learning, and visual key frame extraction, thus achieving intuitive retrieval by browsing thumbnails of semantic key frames. We apply three steps for the efficient retrieval of motion capture data. The first is obtaining the basic type clusters by clustering motion capture data using the novel SK-means algorithm, and after which, immediately performing character matching. The second is learning the retrieval information of users during the retrieval process and updating the successful retrieval rate of each data; the search results are then ranked on the basis of successful retrieval rate by democratic decision making to improve accuracy. The last step is generating thumbnails with semantic generalization, which is conducted by using a novel key frame extraction algorithm based on visualized data analysis. The experiment demonstrates that this method can be utilised for the efficient organization and retrieval of enormous motion capture data.     

基于内容的音频检索:概念和方法

Ｆ过去对视觉媒体的检索,如图象和视频,进行了大量的研究。但是我们注意到音频也是多媒体中的一种典型媒体,是信息的一种常用载体。常规的自理是把数字音频当成非结构化流媒体。然而音频是语音的载体、包含丰富的听觉特征,并且具有结构信息。因此需要并且可以基于这些内容对音频进行存取。本文根据当前相关研究的进展,综述基于内容的音频检索方法,包括面向语音、音乐和音频分析的检索、音频分割等;分析并总结出音频内容及其检     

Visualizing the Semantic Structure in Classical Music Works

A major obstacle in the appreciation of classical music is that extensive training is required to understand musical structure and compositional techniques toward comprehending the thoughts behind the musical work. In this paper, we propose an innovative visualization solution to reveal the semantic structure in classical orchestral works such that users can gain insights into musical structure and appreciate the beauty of music. We formulate the semantic structure into macrolevel layer interactions, microlevel theme variations, and macro-micro relationships between themes and layers to abstract the complicated construction of a musical composition. The visualization has been applied with success in understanding some classical music works as supported by highly promising user study results with the general audience and very positive feedback from music students and experts, demonstrating its effectiveness in conveying the sophistication and beauty of classical music to novice users with informative and intuitive displays.     

COMIB: COMposite Icon Browser for multimedia databases

COMIB(COMposite Icon Browser) is a graphical user interface for retrieval of multimedia databases. It gives users the effect of browsing and navigating multimedia objects simultaneously in a screen using composite icons, that may be thumbnails of the several nested attribute values of those objects. Users can specify these attributes with a mouse while browsing the visualized aggregation hierarchy. Both querying and browsing can be interleaved via query reformulation. We show how these features of COMIB overcome the three drawbacks of the browsing paradigm such as no overview of many objects, the repetitious short-sighted navigation, and the weak presentation of a multimedia object. We also explain the retrieval mechanism algebraically and describe the implementation of COMIB based on this mechanism.     

Instance based personalized multi-form image browsing and retrieval

It is important to adapt and personalize image browsing and retrieval systems based on users’ preferences for improved user experience and satisfaction. In this paper, we present a novel instance based personalized multi-form image representation with implicit relevance feedback and adaptive weighting approach for image browsing and retrieval systems. In the proposed system, images are grouped into forms, which represent different information on images such as location, content etc. We conducted user interviews on image browsing, sharing and retrieval systems for understanding image browsing and searching behaviors of users. Based on the insights gained from the user interview study we propose an adaptive weighting method and implicit relevance feedback for multi-form structures that aim to improve the efficiency and accuracy of the system. Statistics of the past actions are considered for modeling the target of the users. Thus, on each iteration weights of the forms are updated adaptively. Moreover, retrieval results are modified according to the users’ preferences on iterations in order to improve personalized user experience. The proposed method has been evaluated and results are illustrated in the paper. It is shown that, satisfactory improvements can be achieved with proposed approaches in the multi-form scheme.     

Personalizing self-organizing music spaces with anchors: design and evaluation

We propose and evaluate a system for content-based visualization and exploration of music collections. The system is based on a modification of Kohonen’s Self-Organizing Map algorithm and allows users to choose the locations of clusters containing acoustically similar tracks on the music space. A user study conducted to evaluate the system shows that the possibility of personalizing the music space was perceived as difficult. Conversely, the user study and objective metrics derived from users’ interactions with the interface demonstrate that the proposed system helped individuals create playlists faster and, under some circumstances, more effectively. We believe that personalized browsing interfaces are an important area of research in Multimedia Information Retrieval, and both the system and user study contribute to the growing work in this field.