视频挖掘及其应用的系统研究

Mallappa G. Mendagudli, K. Kharade, T. Nadana Ravishankar, K. Vengatesan
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引用次数: 0

摘要

随着数字视频数据的不断增长,有效的视频索引方法将更加有价值。我们已经很多年没有看到这种水平的新多媒体研究了。内容分析旨在通过将语言和事实视为数据来创建高级描述和注释。数据挖掘是一种在大型数据集中寻找以前未知的事实和模式的技术。视频可以包含几种不同类型的数据,如图像、视觉、音频、文本和其他元数据。由于它广泛应用于各个学科,如安全、教育、医学、研究、体育和娱乐,它经常被不同地使用。数据挖掘的目的是发现和阐明隐藏在大量视频片段中的令人兴奋的模式。虽然视频挖掘仍处于起步阶段,但数据挖掘更为成熟。要将挖掘的视频转化为可用的内容,必须进行大量的研究
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Systematic Study of Video Mining with Its Applications
Effective methods for video indexing will be more valuable as digital video data continues to grow. It has been years since we’ve seen this level of new multimedia research. The content analysis aims to create high-level descriptions and annotations by treating language and facts as data. Data mining is a technique that seeks out previously unknown facts and patterns in large datasets. A video can include several different kinds of data, such as images, visuals, audio, text, and additional metadata. Thanks to its broad application in various disciplines, like security, education, medicine, research, sports, and entertainment, it is often used differently. Data mining aims to discover and articulate exciting patterns that are hidden in a lot of video footage. While video mining is still in its infancy, data mining is more mature. A considerable amount of research must be done to turn the mined video into usable content
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