Managing and searching distributed multidimensional annotations with large scale image data

  • Authors:

  • Tian Xia;Fusheng Wang;Peiya Liu;Sridharan Palanivelu

  • Affiliations:

  • College of Computer and Information Science, Northeastern University, Boston, MA;Integrated Data Systems Department, Siemens Corporate Research, Princeton, NJ;Integrated Data Systems Department, Siemens Corporate Research, Princeton, NJ;Integrated Data Systems Department, Siemens Corporate Research, Princeton, NJ

  • Venue:
  • MCAM'07 Proceedings of the 2007 international conference on Multimedia content analysis and mining
  • Year:
  • 2007

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Abstract

Advanced imaging applications are producing large-scale image data for medical diagnosis, part visualization and inspection, content retrieval, analysis, e-reporting, and so on. In many cases, service and non-textual annotations are made on top of the raw images to provide essential information on regions of interest, diseases, defects, evaluations, comments, and etc. These applications pose several challenges: i) Large data volume and the latency of data transfer over the Internet leads to a performance bottleneck; ii) The applications need advanced query support such as similarity queries on the multidimensional annotation data; and iii) Local applications need synchronizing data with a remote central database. In our work, we develop a general distributed multimedia data management system that achieves these goals by providing: i) an intelligent multimedia content caching system to support smooth local applications; ii) a loosely coupled extensible multi-indexing server to support different types of multimedia queries including similarity queries; iii) unified multimedia data access interfaces for universal data access; and iv) an integrated architecture that brings these technologies together into a robust system. The system is now successfully used to support image-based inspection and diagnosis applications such as global part inspection and knowledge database guided medical diagnosis.