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video retrieval
相关语句
  视频检索
     In the research, the Content Based Video Retrieval(CBVR) has being popularly used.
     基于内容的视频检索(Content Based Video Retrieval, CBVR)技术因此应运而生。
短句来源
     Research on Integrated Framework of Intelligent Video Retrieval System Under J2EE Architecture
     J2EE架构下智能视频检索系统集成框架研究
短句来源
     2. Detailed introduce MPEG-7 standard and MPEG-7 based video description tools and models, discuss MPEG-7 based video retrieval technology.
     2.详细介绍了MPEG-7标准及基于MPEG-7标准的视频描述工具和模型,并对基于MPEG-7标准的视频检索技术进行了探讨。
短句来源
     Investigation of the Influence of Compressed-Domain DCT Coefficients on Image and Video Retrieval
     压缩域DCT系数对图像视频检索影响的研究
短句来源
     Recently, applications in video retrieval, face recognition and object fast tracing became common.
     目前,在视频检索与人脸识别以及目标快速跟踪定位等方面的应用已经非常普遍。
短句来源
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  视频特征
     The part of feature retrieval proposed a three-layered framework for multi-feature video retrieval which was composed of presentation,logic and transaction layer.
     特征检索构建了一个用于多视频特征检索的3层体系结构(表示层、逻辑层和事务层)并给出了检索结果融合流程.
短句来源
  “video retrieval”译为未确定词的双语例句
     CBVR means video retrieval from enormous video database through matching of patterns derived from video analysis and feature extraction to represent its content.
     CBVR是指根据视频的内容及上下文关系,在视频分析的基础上,提取能够反映视频内容的各种特征,进而通过模式匹配对大规模视频数据库中的视频数据进行检索。
短句来源
     With the development of multimedia and video database, the technology of content-based video retrieval is receiving increasing attention to structurally analyzing and managing the non-structural video data.
     随着多媒体技术的发展和视频数据库的普及,如何自动地建立索引结构进行视频流的分析和管理,从而在海量的视频数据中查找用户感兴趣的内容,已成为研究人员关注的热点。
短句来源
     Video Retrieval Based on Fuzzy Clustering and Image Features
     基于图象特征的视频流模糊检索
短句来源
     As the base of video query, news video retrieval is divided into structurized analysis and semantic exaction of video information.
     新闻视频索引是视频查询的基础,包含新闻视频信息的结构化分析和语义提取,其中结构化分析包括新闻条目分段、镜头分段和关键帧提取;
短句来源
     3. Design a MPEG-7-based video retrieval system and implement its main function.
     3.设计了一个基于MPEG-7标准的视频描述生成和检索系统,并实现了其中的主要功能。
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  video retrieval
We have found that successful content-based video data-management systems depend on three most important components: key-segments extraction, content descriptions and video retrieval.
      
In this paper we propose a system to extract object-based and global features from compressed MPEG video using the motion vector information for video retrieval.
      
Compressed domain video retrieval using object and global motion descriptors
      
Video retrieval of near-duplicates using κ-nearest neighbor retrieval of spatio-temporal descriptors
      
In this paper, an object-based video retrieval methodology for search in large, heterogeneous video collections is presented.
      
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CBIR(Content Based Image Retrieval) which indexes images or video shots desired from large image or video library, is becoming a more and more important technique in large image database organization and management. In this paper, we reviewed the development of CBIR and discussed some main techniques of CBIR, including color index, shape index, texture index (which are used in image retrieval) and shot detection, mosaic, dominant motion estimation and layered representation (which are used in video retrieval)....

CBIR(Content Based Image Retrieval) which indexes images or video shots desired from large image or video library, is becoming a more and more important technique in large image database organization and management. In this paper, we reviewed the development of CBIR and discussed some main techniques of CBIR, including color index, shape index, texture index (which are used in image retrieval) and shot detection, mosaic, dominant motion estimation and layered representation (which are used in video retrieval).

基于内容的图象检索技术,即从大量的静止或活动视频图象库中检索包含目标物体的图象(或视频片段),在高度信息化的今天,已成为内容图象库中图象信息组织和管理不可缺少的技术.本文介绍了基于内容检索技术的进展,并对其主要方法如基于颜色、形状、纹理等静止图象检索技术和片段检测、拼接、主运动估计和层描述等视频检索技术进行了讨论

Segmenting video sequences into individual shots is one of the fundamental processes in content based video retrieval. We can further parse and index the video content based on the basic unit of shot. Up to now, more and more video materials are stored and transmitted in the compression form, so it is practical to study the shot segmentation algorithms based on compressed video data. This paper presents an integrated approach to detect the boundaries between shots by using the discret...

Segmenting video sequences into individual shots is one of the fundamental processes in content based video retrieval. We can further parse and index the video content based on the basic unit of shot. Up to now, more and more video materials are stored and transmitted in the compression form, so it is practical to study the shot segmentation algorithms based on compressed video data. This paper presents an integrated approach to detect the boundaries between shots by using the discret cosine transform (DCT) coefficients and motion vectors encoded in MPEG compressed data. Only minimal decoding is needed for the algorithm. Considering the complicated situation in real world video sequences, three algorithms are developed to deal with different situations, and we also present a tree like classifier to organize the three algorithms together to form a system. By testing ten video sequences for various types, we get over 90% correct percentage.

镜头切分是实现对动态视频基于内容检索的第一步,以检测出来的镜头作为基本单元,可以进一步对视频内容进行分析和建立索引。从实用角度看,目前越来越多的动态视频资料都是以压缩形式存储和传输,所以,研究基于压缩视频流的算法更有实际意义。本文旨在提出一种基于MPEG国际标准压缩视频流的镜头自动切分算法,通过利用MPEG数据流中已有的信息,如离散余弦变换(DCT)系数和运动向量,只进行最小程度的解码,来检测镜头间的边界,从而实现镜头切分。针对实际视频流中镜头切换方式的复杂性,本文提出了三个算法分别处理不同情况,并将这三个算法以树形分类器的方式组织在一起,形成一个系统。通过对十段不同类型的MPEG-Ⅰ压缩视频节目进行镜头切分实验,取得了90%以上的正确率。

The traditional way of video retrieval is to annotate the video, get textual information such as caption,

视频检索的传统方法之一是首先从视频中摘取出文本信息(如标题、关键词等等),然后基于这一关键字集上回答用户的查询.由于自动摘取文本信息的过程至今尚未自动化,因而从视频中摘取信息主要由人工来完成,这在实际应用上证明是不现实的.另一种方法则是上一情形的极端,即它是利用低层的视频内容,诸如颜色、纹理、形状、运动特征等等,目的在于克服人工摘取关键字所涉及的困难.文中提出了基于ToC视频结构的语义表达,从视频的字幕中提取出语义信息,然后用WordNet,一个电子词汇系统来提供语义联想.该方法已应用于WebMARS的视频信息检索系统中,运行结果表明系统的检索性能大大得以改善.

 
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