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A Feature Extraction from Compressed Multimedia Data For Content-based Multimedia Data Retrieval

用于基于内容的多媒体数据检索的压缩多媒体数据特征提取

基本信息

批准号：
11680413
负责人：
HOSHI Mamoru
金额：
$ 1.79万
依托单位：
University of Electro-Communications
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
1999
资助国家：
日本
起止时间：
1999 至 2000
项目状态：
已结题

项目摘要

Multimedia Database(MDB)is a fundamental and important system to manage large set of multimedia data. There are two problems to make an effective MDB.One is how to efficiently store multimedia data, another is how to effectively retrieve multimedia. For solving these problems, we propose a simple and clear framework for a content-based multimedia data retrieval system using MPEG4 domain and provide a new music feature for a content-based music retrieval on the new framework. A big difference between the new framework of a content-based multimedia data retrieval system and a typical framework of that is a feature extraction method. On the new framework, a feature for describing a content of multimedia data is extracted from the compressed data or a compression method, while on a typical framework a feature is extracted from row data(e.g.raw image data, signal data of music, etc.).We target on a content-based music retrieval system on the new framework and make a prototype system which a … More llows us queries by example of the compressed music data whose bit rate are various. For making a content-based music retrieval system, we provide a new music feature which satisfies the following requirements ;1. computable from MPEG-4/audio domain,2. robust for bit rate,3. computable from the compressed data without decoding.We show theoretically that the i-th autocorrelation coefficient with bit rate B_1 can approximate the j-th autocorrelation coefficient with bit rate B_2, where j=[(B_1)/(B_2)i]. So, we call a relation of autocorrelation coefficients with respect to bit rates an approximation relation with bit rate. And we experimentally confirm that the extracted autocorrelation coefficients from MPEG4/audio domain actually satisfy the approximation relation with bit rate.Then, we provide a new music feature by using the approximation relation with bit rate, and experiment on the music retrievals to evaluate the performance of retrievals by using the music feature with various bit rates. The results of experiments show a good performance of retrievals, and that the proposed music feature have a good performance of retrieval for queries with various bit rate. Less

多媒体数据库(MDB)是管理大量多媒体数据的基础且重要的系统。制作一个有效的MDB有两个问题。一个是如何有效地存储多媒体数据，另一个是如何有效地检索多媒体。为了解决这些问题，我们提出了一个使用MPEG4域的基于内容的多媒体数据检索系统的简单而清晰的框架，并为新框架上基于内容的音乐检索提供了新的音乐特征。基于内容的多媒体数据检索系统的新框架与典型框架之间的一个很大的区别是特征提取方法。在新框架上，描述多媒体数据内容的特征是从压缩数据或压缩方法中提取的，而在典型框架上，特征是从行数据（例如原始图像数据、音乐信号数据等）中提取的。我们在新框架上以基于内容的音乐检索系统为目标，并制作了一个原型系统，该原型系统允许我们通过不同比特率的压缩音乐数据的示例进行查询。为了制作基于内容的音乐检索系统，我们提供了一个新的音乐功能，它满足以下要求；1。可从 MPEG-4/音频域计算，2。比特率稳健，3。理论上，比特率B_1的第i个自相关系数可以近似比特率B_2的第j个自相关系数，其中j=[(B_1)/(B_2)i]。因此，我们将自相关系数与比特率的关系称为与比特率的近似关系。并且我们通过实验证实从MPEG4/音频域中提取的自相关系数实际上满足与比特率的近似关系。然后，我们利用与比特率的近似关系提供新的音乐特征，并在音乐检索上进行实验，以评估使用不同比特率的音乐特征的检索性能。实验结果表明具有良好的检索性能，并且所提出的音乐特征对于各种比特率的查询具有良好的检索性能。较少的