Joint exploitation of multiple media from multimedia to databases

P. Gros
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Abstract

Multimedia content analysis offers many exciting research opportunities and is a necessary step towards automatic understanding of the content of digital documents. Digital documents are typically composite. Processing in parallel and integrating low-level information computed over each of the media that compose a multimedia document can yield knowledge that stand-alone and isolated analysis could not discover.Joint processing of multiple media is very challenging, even at the lowest analysis levels. Coping with imperfect synchronization of pieces of information, mixing extremely different kinds of information (numerical or symbolic descriptions, values describing intervals or instants, probabilities and distances, HMM and Gaussians, ...), and reconciling contradictory outputs are some of the obstacles which make processing of multimedia documents much more difficult than it seems at first glance.This talk will first show what may be gained from jointly analyzing multimedia documents. It will then briefly overview the typical information that can be extracted from major media (video, sound, images and text) before focusing on the problems that arise when trying to use all this information together. We hope to convince researchers to start trying to solve these problems, since they directly hamper the acquisition of higher-level knowledge from multimedia documents.
从多媒体到数据库的多种媒体的联合开发
多媒体内容分析提供了许多令人兴奋的研究机会,是自动理解数字文档内容的必要步骤。数字文档通常是复合的。并行处理和集成在构成多媒体文档的每种媒体上计算的低级信息可以产生独立和孤立分析无法发现的知识。多媒体的联合处理是非常具有挑战性的,即使在最低的分析水平。处理不完美的信息同步,混合极端不同种类的信息(数字或符号描述,描述间隔或瞬间的值,概率和距离,HMM和高斯,…),以及调和矛盾的输出,这些都是使多媒体文档处理比乍一看要困难得多的一些障碍。本演讲将首先展示联合分析多媒体文档可以获得什么。然后简要概述可以从主要媒体(视频,声音,图像和文本)中提取的典型信息,然后重点讨论在尝试使用所有这些信息时出现的问题。我们希望说服研究人员开始尝试解决这些问题,因为它们直接阻碍了从多媒体文档中获取更高层次的知识。
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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