Multimedia Information Retrieval Systems

该项目设计了多媒体的存储和检索方法 数据库，与Christodoulakis博士合作， MUSIC-FORTH中心，Chanea，希腊。具体而言，它侧重于 多媒体对象的高性能相似性检索 内容 对于文本，它使用签名文件方法、反转和 混合方法（Hybrid Methods）。对于图像和其他媒体（语音， 等等），它检查了用于高维空间的索引方法， 将对象视为特征空间中的多维点。等 特征可以是，例如，的傅里叶变换系数， 形象敏捷性进一步改善了大型 对象，使用去聚类方法，例如，基于分形或 纠错码这项工作的结果将检索 以及用于几种类型的媒体的去聚类方法。 这些方法 将作为多媒体和对象的构建块- 面向不久的将来的DBMS。 这个项目，它是共同的， 由欧洲共同体Esprit计划赞助，将促进 美国和欧洲的研究人员之间的合作， 加强科研成果交流，加快发展 新一代的DBMS

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.