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video hierarchical structure
相关语句
  视频层次结构
     Video Hierarchical Structure Mining
     视频层次结构挖掘
短句来源
     A simple framework for video hierarchical structure mining is to partition continuous video frames into discrete physical shots,extract features from video shots,and scene structure construction based on shots.
     视频层次结构挖掘的一个简单框架是对视频进行镜头分割、抽取镜头特征和视频场景构造。
短句来源
     In this paper,two crucial algorithms of video hierarchical structure mining,shot clustering based on multi-features and scene change detection based on shot,are proposed.
     论文在镜头分割的基础上提出了基于多特征的镜头聚类分析和基于镜头的场景边界检测两种视频场景构造方法,从而实现视频层次结构挖掘。
短句来源
  相似匹配句对
     Video Hierarchical Structure Mining
     视频层次结构挖掘
短句来源
     Scheme and Techniques for Hierarchical Oranization of Video
     视频分层组织方案和技术
短句来源
     A Hierarchical Authorization System on Digital Video
     数字视频信息分级授权收视系统
短句来源
     Video 75
     Video75三角架
短句来源
     Video show
     视频交流
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During the recent ten years, analysis of video content has become a hot research topic Generally speaking, in the video hierarchical structure, scene is the highest layer of video processing However, with the current research progress in video processing, It is believed that a higher layer video processing unit, “Program”, is needed to represent a video “program” is defined as one of more continuous scenes For example, in a several hour very comprehensive video stream,...

During the recent ten years, analysis of video content has become a hot research topic Generally speaking, in the video hierarchical structure, scene is the highest layer of video processing However, with the current research progress in video processing, It is believed that a higher layer video processing unit, “Program”, is needed to represent a video “program” is defined as one of more continuous scenes For example, in a several hour very comprehensive video stream, there are thousands of scence It is difficult to manage this large amount of information without the program layer Another example is video genre verification Almost all of the proposed algorithms in this research area are based on the assumption that programs have been manually segmented So, implementing automatic program segmentation is of great benefit in reality A new video processing unit, “program”, is proposed to be inserted between scene layer and video layer A TV program specific automatic segmentation algorithm is also proposed

近年来 ,视频内容的结构化分析逐渐成为一个研究热点 传统意义上认为场景是最高层次的视频处理单元 然而随着研究工作的不断深入 ,需要提出一种更高层次的视频处理单元———节目 ( program) 通过节目管理大量存在的场景 ,形成更丰富的层次 ;另外 ,节目还可以作为视频节目分类算法的输入 ,从而实现从分割到分类的全部自动化 在传统层次结构的基础上 ,进一步拓宽视频处理单元的概念 ,在场景层与视频层之间增加节目层 并且提出一种针对特定电视频道的视频流的节目自动分割算法 ,实验结果表明该算法具有较好的性能

To structuralize video streams plays an important role in the processing of video.The basic structure for video is a hierarchical structure which consists of four kinds of components,namely frame,shot,scene,and video program.A simple framework for video hierarchical structure mining is to partition continuous video frames into discrete physical shots,extract features from video shots,and scene structure construction based on shots.In this paper,two crucial algorithms of video hierarchical...

To structuralize video streams plays an important role in the processing of video.The basic structure for video is a hierarchical structure which consists of four kinds of components,namely frame,shot,scene,and video program.A simple framework for video hierarchical structure mining is to partition continuous video frames into discrete physical shots,extract features from video shots,and scene structure construction based on shots.In this paper,two crucial algorithms of video hierarchical structure mining,shot clustering based on multi-features and scene change detection based on shot,are proposed.Our experimental results demonstrate the performance of scene change detection based on shot is better than that of shot clustering based on multi-features.

视频处理的关键是视频信息的结构化,视频基本结构是由帧、镜头、场景和视频节目构成的层次结构。视频层次结构挖掘的一个简单框架是对视频进行镜头分割、抽取镜头特征和视频场景构造。论文在镜头分割的基础上提出了基于多特征的镜头聚类分析和基于镜头的场景边界检测两种视频场景构造方法,从而实现视频层次结构挖掘。实验表明,基于镜头的场景边界检测性能优于基于多特征的镜头聚类分析。

 
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