Multimedia Information Retrieval Systems

该项目与希腊Chanea MUSIC-FORTH中心负责人Christodoulakis博士合作，设计多媒体数据库的存储和检索方法。具体来说，它侧重于基于内容的多媒体对象的高性能相似度检索。对于文本，它使用签名文件方法、反转和组合（混合方法）。对于图像和其他媒体（语音等），它研究了高维空间的索引方法，将对象视为特征空间中的多维点。这些特征可以是，例如，图像的傅里叶变换系数。通过使用聚类方法，例如基于分形或纠错码，并行性进一步提高了大型对象的响应时间。这项工作的结果将是几种类型媒体的检索和分类方法。这些方法将在不久的将来作为多媒体和面向对象dbms的构建块。该项目由欧洲共同体Esprit项目共同赞助，将促进美国和欧洲研究人员之间的合作，加强研究成果的交流，并加快新一代数据库管理系统的开发。

The project designs storage and retrieval methods for multimedia databases, in collaboration with Dr. Christodoulakis, head of the MUSIC-FORTH Center, Chanea, Greece. Specifically, it focuses on high-performance similarity retrieval of multimedia objects by content. For text, it uses signature file methods, inversion and combinations (hybrid methods). For images and other media (voice, etc.), it examines indexing methods for high-dimensionality spaces, treating objects as multi-dimensional points in feature space. Such features could be, e.g., the Fourier-transform coefficients of an image. Parallelism further improves the response time for large objects, using declustering methods, e.g., based on fractals or error correcting codes. The results of this work will be retrieval and declustering methods for several types of media. These methods will serve as building blocks for the multimedia and object- oriented DBMSs of the near future. This project, which is co- sponsored by the European Community Esprit program, will foster collaboration between researchers in the United States and Europe, enhance exchange of research results, and speed up development of a new generation of DBMSs.