Data mining framework for video data

D. Saravanan, S. Srinivasan
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引用次数: 22

Abstract

Content-based video analyzing and retrieval are important technologies, which have been an international research focus in recent ten years. It is needed urgently the advanced technologies for organizing, analyzing, representing, indexing, filtering, retrieving and mining the vast amount of videos to retrieve specific information based on video content effectively, and to provide better ways for entertainment and multimedia applications. Although numerous papers have been published on data mining few of them deal with video mining is focusing on low features, such as color, texture, audio and motion. Due to the inherent complexity of video data, existing data mining algorithms and techniques cannot be used directly in video. In this paper we try to focus new mining techniques designed to facilitate the video data mining process.
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视频数据的数据挖掘框架
基于内容的视频分析与检索技术是近十年来国际上研究的热点。迫切需要对海量视频进行组织、分析、表示、索引、过滤、检索和挖掘的先进技术,以有效地检索基于视频内容的特定信息,为娱乐和多媒体应用提供更好的方式。尽管已经发表了大量关于数据挖掘的论文,但涉及视频挖掘的论文很少关注低特征,如颜色、纹理、音频和运动。由于视频数据固有的复杂性,现有的数据挖掘算法和技术不能直接用于视频。在本文中,我们试图关注旨在促进视频数据挖掘过程的新挖掘技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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