一种基于小波的视频片断检索方法

视频片断检索是基于内容的视频检索的主要方式,该文首先利用颜色信息对视频库进行初步筛选,然后根据集合的相似性度量进行精确检索,通过实验,该方法可以获得更快的检索速度。     

An integrated approach to concept evaluation in a new product development

A new product development (NPD) process can be thought as a comprehensive process in which the design is progressively detailed through a series of phases. At the end of each phase a design review is held to approve the design and release or not it to the next level. As one of these phases, concept selection aiming to select the most appropriate concept for further development, is conducted earlier in the process. As the further development progresses on a selected concept, it becomes more difficult to make design changes in terms of cost and schedule dimensions, and therefore, selecting the best concept among a set of available alternatives has been an important issue for companies. On the other hand, in the presence of many alternatives and selection criteria, the selection problem becomes a multiple-criteria decision making concept selection problem. To solve this problem, in this work, an integrated approach bringing two popular methods together: the modified technique for order preference by similarity to ideal solution (TOPSIS) and the analytical network process (ANP). The ANP method is used to determine the relative weights of a set of quantitative and qualitative evaluation criteria, as the modified TOPSIS method utilized to rank competing concept alternatives. In addition, a real example is presented to demonstrate the effectiveness and applicability of the proposed approach for potential practitioners and readers.     

Unsupervised semantic-based convolutional features aggregation for image retrieval

Multimedia Tools and Applications - Deep features extracted from the convolutional layers of pre-trained CNNs have been widely used in the image retrieval task. These features, however, are in a...     

基于语义的信息获取服务平台的研究与实现

随着信息化建设的深入发展,应用系统积累的数据和信息资源越来越多.如何在不影响现有应用系统的配置和管理模式下,针对大量的分散和异构的应用,为用户提供快速准确的信息获取服务,已经成为一个亟待解决的问题.为此,提出了基于语义的信息获取服务平台,通过引入基于语义的全局数据视图对文档加以快速索引,并对索引进行切分和备份,同时采用针对性的相关性排序算法,为用户提供更好的信息获取服务.     

基于SVM的视频关键帧语义检索系统

为缩小"语义鸿沟",探讨了将支持向量机(SVM)应用于视频语义检索,提出了利用多变量支持向量机回归方法(SVR)进行语义自动标注,再将SVM分类应用于关键帧的语义检索的反馈中,改进了传统的SVM反馈方法.一方面记忆并累加样本集,优化负例选择,平衡正负样本数目,使训练集样本保持动态增长的平衡状态;另一方面,保存每次满意查询的SVM模型,使本次的反馈信息得以继续使用,从而建立SVM反馈的长期记忆机制.实验结果表明,与基于内容的SVM反馈检索相比,改进后的基于SVM反馈的视频语义关键帧检索的准确率和检索效率都有所提高.     

一种基于本体的视频检索技术研究

传统的视频检索大多采用基于关键词的方法,难以获得让用户满意的查准率和查全率。为此提出一种基于本体的视频检索技术,该技术借助于领域本体,以其基本概念为关键词通过互联网图像搜索引擎在线获取样本图像组,提取SIFT特征建立图像特征词典,抽取图像特征直方图并计算相似度,辅助完成视频的自动标注,初始化视频检索库;同时,借助于领域本体,对从用户的查询输入中抽取的关键词进行语义扩展,将以扩展概念集进行检索的结果返回给用户,以此实现基于本体的视频检索。最后,结合实例对该算法进行实现和分析,表明了该方法的可行性和有效性。     

A semantic approach to concept lattice-based information retrieval

The volume of available information is growing, especially on the web, and in parallel the questions of the users are changing and becoming harder to satisfy. Thus there is a need for organizing the available information in a meaningful way in order to guide and improve document indexing for information retrieval applications taking into account more complex data such as semantic relations. In this paper we show that Formal Concept Analysis (FCA) and concept lattices provide a suitable and powerful support for such a task. Accordingly, we use FCA to compute a concept lattice, which is considered both a semantic index to organize documents and a search space to model terms. We introduce the notions of cousin concepts and classification-based reasoning for navigating the concept lattice and retrieve relevant information based on the content of concepts. Finally, we detail a real-world experiment and show that the present approach has very good capabilities for semantic indexing and document retrieval.     

An empirical analysis of information retrieval based concept location techniques in software comprehension

Concept location, the problem of associating human oriented concepts with their counterpart solution domain concepts, is a fundamental problem that lies at the heart of software comprehension. Recent research has attempted to alleviate the impact of the concept location problem through the application of methods drawn from the information retrieval (IR) community. Here we present a new approach based on a complimentary IR method which also has a sound basis in cognitive theory. We compare our approach to related work through an experiment and present our conclusions. This research adapts and expands upon existing language modelling frameworks in IR for use in concept location, in software systems. In doing so it is novel in that it leverages implicit information available in system documentation. Surprisingly, empirical evaluation of this approach showed little performance benefit overall and several possible explanations are forwarded for this finding.

ICICLE: A semantic-based retrieval system for WWW images

In this paper, we present ICICLE (Image ChainNet and Incremental Clustering Engine), a prototype system that we have developed to efficiently and effectively retrieve WWW images based on image semantics. ICICLE has two distinguishing features. First, it employs a novel image representation model called Weight ChainNet to capture the semantics of the image content. A new formula, called list space model, for computing semantic similarities is also introduced. Second, to speed up retrieval, ICICLE employs an incremental clustering mechanism, ICC (Incremental Clustering on ChainNet), to cluster images with similar semantics into the same partition. Each cluster has a summary representative and all clusters' representatives are further summarized into a balanced and full binary tree structure. We conducted an extensive performance study to evaluate ICICLE. Compared with some recently proposed methods, our results show that ICICLE provides better recall and precision. Our clustering technique ICC facilitates speedy retrieval of images without sacrificing recall and precision significantly.     

An integrated approach for head gesture based interface

The head pose and movement of a user is closely related with his/her intention and thought, recognition of such information could be useful to develop a natural and sensitive user-wheelchair interface. This paper presents an original integrated approach to a head gesture based interface (HGI) which can perform both identity verification and facial pose estimation. Identity verification is performed by two-factor face authentication which is implemented by the combination of topographic independent component analysis (TICA) and multispace random projection (MRP). Modified synergetic computer with melting (Modified SC-MELT) is introduced to classify facial poses. Motion profile generator (MPG) is thoroughly developed during the integration to convert each estimated facial pose sequence into motion control signal to actuate motor movements. The HGI is intended to be deployed as a user-wheelchair interface for disabled and elderly users in which only users with genuine face and valid token may be granted authorized access and hence pilot an electric powered wheelchair (EPW) using their faces. The integration has been verified under a number of experiments to justify the feasibility and performance of the proposed face-based control strategy.     

基于语义的组件组合方法研究

在基于组件的一般性应用系统中,面向自然语言描述需求的组件自动组合技术的研究仍然存在很多挑战。但是,在限定的上下文中,以基于语义的方式对特定应用提供组件自动组合的方法仍然是可行的。采用关键字描述语义信息,提出了一种基于语义的组件组合方法,对组件和请求过程建模,采用规划器搜索组件序列,完成组件的自动组合。方法已经应用于航天器自动化测试数据查询应用系统中,取得了较好的应用效果。     

A transductive multi-label learning approach for video concept detection

In this paper, we address two important issues in the video concept detection problem: the insufficiency of labeled videos and the multiple labeling issue. Most existing solutions merely handle the two issues separately. We propose an integrated approach to handle them together, by presenting an effective transductive multi-label classification approach that simultaneously models the labeling consistency between the visually similar videos and the multi-label interdependence for each video. We compare the performance between the proposed approach and several representative transductive and supervised multi-label classification approaches for the video concept detection task over the widely used TRECVID data set. The comparative results demonstrate the superiority of the proposed approach.     

A compressed sensing approach for query by example video retrieval

Recently, compressed Sensing (CS) has theoretically been proposed for more efficient signal compression and recovery. In this paper, the CS based algorithms are investigated for Query by Example Video Retrieval (QEVR) and a novel similarity measure approach is proposed. Combining CS theory with the traditional discrete cosine transform (DCT), better compression efficiency for spatially sparse is achieved. The similarity measure from three levels (frame level, shot level and video level, respectively) is also discussed. For several different kinds of natural videos, the experimental results demonstrate the effectiveness of system by the proposed method.     

Development of a semantic-based content mapping mechanism for information retrieval

Most information retrieval systems use keywords entered by the user as the search criteria to find documents. However, the language used in documents is often complicated and ambiguous, and thus the results obtained by using keywords are often inaccurate. To address this problem, this study developed a semantic-based content mapping mechanism for an information retrieval system. This approach employs the semantic features and ontological structure of the content as the basis for constructing a content map, thus simplifying the search process and improving the accuracy of the returned results.     

基于概念的论文相似性检索

Web上越来越多的论文给我们提出了一个新的课题：如何检索满足需求的论文。传统的基于查询项匹配检索方法往往无法准确地检索出满足用户需求的论文。这里给出了一种基于概念的论文相似性检索方法,有效地改进了传统的论文检索方法。介绍了一种对论文关键词进行层次聚类的算法,首先把论文关键词聚类为概念,从而生成一个概念树,然后用概念向量表示论文,每篇论文对应一个概念子树。在相似性检索时,采用改进的余弦相似性方法,根据概念向量计算论文的相似性,把与给定论文最相似的论文返回给用户。用这种算法,能很好地对论文进行基于概念的相似性检索。算法克服了基于查询项匹配检索的缺点,实验证明其有较高的查全率和查准率。     

An integrated fire detection and suppression system based on widely available video surveillance

An integrated system based on video surveillance is presented for automatic fire detection and suppression. The system is composed of two modules, including fire detection and fire suppression. The fire detection module makes full use of traditional CCD cameras for fire recognition. Some spatio-temporal features, such as color and motion, are extracted to detect fire in real time by utilizing sequential image processing techniques. Once a fire is detected, the system will control the fire suppression module to extinguish the fire automatically. It mainly consists of control device, mobile device, and water gun. Experiments performed in a large space hall show that the integrated system can detect a fire about a few seconds after ignition and automatically suppress the fire quickly.     

基于本体的视频语义检索系统研究

在语义层次上检索视频内容,可以突破“语义鸿沟”,提高视频内容的利用效率。利用本体的标注和推理能力,研究视频语义检索,充分挖掘视频内容的结构和语义信息,构建层次化的语义索引,能极大提高系统的语义检索能力。该视频语义检索系统(OVSR)的本体架构集成了领域本体、视频本体和核心本体,具有很强的扩展和交互能力。主要论述OVSR的本体架构,视频语义模型和索引模型,研究OVSR的查询重写算法以及本体推理算法。