CISE Research Instrumentation: Experimental Infrastructure for Indexing, Retrieval and Robust Presentation of Multimedia Data

9818289 Zhang，AidongSrihari，Rohini K.纽约州立大学BuffaloCISE研究基础设施：多媒体数据的索引，检索和机器人表示的实验基础设施该研究仪器使以下方面的研究项目成为可能：- 多媒体数据的一致和鲁棒的检索、传输和呈现-多媒体图像注释、索引和检索，多维数据挖掘及其在大型数据库中的应用扩展多媒体数据库这项研究仪器拨款资助购买一个高性能存储系统，以建立一个实验基础设施，用于进行多媒体信息的研究管理和检索。 所要求的仪器，使三个项目，需要大容量的机器与大内存和巨大的磁盘空间：支持定制的多媒体演示在分布式环境中;多媒体数据注释，索引和检索;和数据挖掘和应用程序在大型多媒体数据库。 第一个项目建立了一个基本框架，并开发了确保多媒体数据的一致和可靠的检索、传输和呈现的技术。 实验研究将进行异构多媒体数据的并发演示，强大的端到端传输协议，合并用户交互和延迟效应的同步策略。 第二个项目研究了在一个大型图片检索系统的索引和检索阶段中文本和图片信息的整合。 将进行实验分析，以证明这些技术的实用性。 第三个项目研究了从现实生活中的图像生成的大量多维数据的多分辨率聚类方法。 将研究聚类方法的性能，并通过不同类型的数据分布来证明这些方法的有效性。

9818289Zhang, AidongSrihari, Rohini K.State University of New York at BuffaloCISE Research Infrastructure: Experimental Infrastructure for Indexing, Retrieval, and Robost Presentation of Multimedia DataThis research instrumentation enables research projects in:- Consistent and Robust Retrieval, Transmission and Presentation of Multimedia Data- Multimedia Image annotation, Indexing and Retrieval, and - Multidimensional Data Mining and Applications in Large-Scale Multimedia DatabasesThis research instrumentation grant contributes to the purchase of a high performance storage system to establish an experimental infrastructure for conducting research on multimedia information management and retrieval. The requested instrumentation enables three projects which require high-capacity machines with large memory and huge disk space: supporting customized multimedia presentations in distributed environments; multimedia data annotation, indexing and retrieval; and data mining and applications in large-scale multimedia databases. The first project establishes an underlying framework and develops techniques for ensuring consistent and robust retrieval, transmission and presentation of multimedia data. Experimental research will be conducted on concurrent presentations of heterogeneous multimedia data, robust end-to-end transmission protocols, incorporation of user interactions and delay effects in synchronizing strategies. The second project investigates the integration of text and photographic information in both the indexing and retrieval stages of a large-scale picture retrieval system. Experimental analysis will be conducted to demonstrate the utility of these techniques. The third project investigates multi-resolution clustering approaches on vast amount of multi-dimensional data generated from real-life images. The peformance of the clustering approaches will be studied and the effectiveness of these approaches will be demonstrated through different types of distributions of data.