In this paper, a motion segmentation approach for content based video representation specified in the standard of MPEG 4 is proposed.
提出了一种MPEG4标准所规范的基于内容表示的图像序列运动分割算法。
This object representation contains details of the video being requested, such as its URL, author, provider, and title.
该对象表示包含被请求视频的详细信息,比如它的URL、作者、提供者和标题。
Selecting episode representation frame is one of the important processes in video semantic analysis and content-based video retrieval.
情节代表帧选取方法是视频语义分析和基于内容的视频检索的很重要的方法。
It is becoming the emergent and important issues for efficient organization, representation, store and management of video data as well as rapid retrieval and browsing of video data.
然而如何有效地对这些视频数据进行组织、表达、存储和管理,以及如何对其进行快速检索与浏览等已成为视频领域内急待解决的重大课题。
For video sequences, we introduce such techniques as shot detection, representation of shot content, semantic scene description.
对于视频序列,则介绍了镜头检测、镜头内容表示、场景的语义描述等技术。
In this paper, a semantic shot representation and event query framework for soccer video is proposed.
提出了一个足球视频中的语义镜头表示及事件查询框架。
In this thesis, we mainly develop the methods for video content analysis as well as video content representation on a semantic level.
本文主要针对语义层次上的视频内容结构化分析和表达进行了研究。
The research contents include high dimension feature vectors index, semantic video classification, relevance feedback, similarity measure of video clips and video content representation.
本文研究内容涉及特征索引方法、视频语义分类方法、相关反馈方法、视频片段的相似度量以及视觉内容特征的表示等问题。
Rayspace representation is an effective approach to realizing realtime free viewpoint video system with complicated scenes.
光线空间表示是实现实时复杂场景自由视点视频的有效方法。
The Non-symmetry and Anti-packing Model (NAM) is suitable for representations of image pattern, audio pattern, video pattern, and text pattern, and it is a general pattern representation model.
非对称逆布局模型(NAM)适用于图像模式、语音模式、文本模式、视频模式的表示,是一个通用型的模式表示模型。
As a brief representation of video content, video summarization can effectively assist users' browsing and organizing video clips.
视频摘要作为一种视频内容的简要表示,能够有效地增强用户浏览和组织视频的效率。
Afterwards, equivalence classes are mapped into matrix representation. Therefore various factors are computed to rank the similarity of the selected video clips by characters of the matrix.
然后把等价类映射为矩阵表达形式,再通过矩阵的特性来度量影响片段相似度的不同因子,实现了相似片段的排序。
Afterwards, equivalence classes are mapped into matrix representation. Therefore various factors are computed to rank the similarity of the selected video clips by characters of the matrix.
然后把等价类映射为矩阵表达形式,再通过矩阵的特性来度量影响片段相似度的不同因子,实现了相似片段的排序。
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