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Video query processing in the VDBMS testbed for video database research

Published:07 November 2003Publication History

ABSTRACT

The increased use of video data sets for multimedia-based applications has created a demand for strong video database support, including efficient methods for handling the content-based query and retrieval of video data. Video query processing presents significant research challenges, mainly associated with the size, complexity and unstructured nature of video data. A video query processor must support video operations for search by content and streaming, new query types, and the incorporation of video methods and operators in generating, optimizing and executing query plans. In this paper, we address these query processing issues in two contexts, first as applied to the video data type and then as applied to the stream data type. We first present the query processing functionality of the VDBMS video database management system as a framework designed to support the full range of functionality for video as an abstract data type. We describe two query operators for the video data type which implement the rank-join and stop-after algorithms. As videos may be considered streams of consecutive image frames, video query processing can be expressed as continuous queries over video data streams. The stream data type was therefore introduced into the VDBMS system, and system functionality was extended to support general data streams. From this viewpoint, we present an approach for defining and processing streams, including video, through the query execution engine. We describe the implementation of several algorithms for video query processing expressed as continuous queries over video streams, such as fast forward, region-based blurring and left outer join. We include a description of the window-join algorithm as a core operator for continuous query systems, and discuss shared execution as an optimization approach for stream query processing.

References

  1. Aref, W., Catlin, A.C., Elmagarmid, A., Fan, J., Hammad, M., Ilyas, I., Marzouk, M., and Zhu, X. A video database management system for advancing video database research. In Proc. of the Int Workshop on Management Information Systems. Nov 2002. Tempe, Arizona.]]Google ScholarGoogle Scholar
  2. Aref, W., Catlin, A.C., Elmagarmid, A., Fan, J., Guo, J., Hammad, M., Ilyas, I., Marzouk, M., Prabhakar, S., Rezgui, A., Teoh, S., Terzi, E., Tu, Y., Vakali, A. and Zhu, X. A distributed server for continuous media. In Proc. of the 18th Int Conf on Data Engineering. Feb 26-Mar 1 2002. San Jose, California.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Beckmann, N., Kriegel, H., Schneider, R. and Seeger, B. The R* -tree: an efficient robust access method for points and rectangles. SIGMOD Record, ACM Special Interest Group on Management of Data, 19(2): pp. 322---331. 1990.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Berchtold, S., Böhm, C., Jagadish, H., Kriegel, H-P. and Sander, J. Independent quantization: An index compression technique for high-dimensional data spaces. In Proc. of the 16th Int Conf on Data Engineering. San Diego, CA. pp. 577--588. February 2000.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Bertino, E., Elmagarmid, A. and Hacid, M-S. Quality of service in multimedia digital libraries. SIGMOD Record. 30(1), pp. 35--40, March 2003.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Bertino, E., Hammad, M., Aref, W. and Elmagarmid, A. An access control model for video database systems. In Proc. of the 9th Int Conf on Information and Knowledge Management. pp. 336---343. Nov 2000.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Bertino, E., Samarati. P. and S. Jajodia. An extended authorization model. IEEE Trans. on Knowledge and Data Engineering. 9(1). pp. 85--101. 1997.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. P. Bonnet , J. E. Gehrke and P. Seshadri. Towards Sensor Database Systems. In Proc. of the 2nd Inter Conf on Mobile Data Management. Jan 2001.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Michael J. Carey and Donald Kossmann, On saying "Enough already!" in SQL, In Proc. CK SIGMOD. Tucson, Arizona. May 1997.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Michael J. Carey and Donald Kossmann, Reducing the Braking Distance of an SQL Query Engine, In Proc. CK'98 VLDB. New York, August, 1998.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Fagin, R., Lotem, A. and Naor, M. Optimal aggregation algorithms for middleware. In Proc. PODS'01 Santa Barbara, CA. May 2001.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Fan, J., Aref, W., Elmagarmid, A., Hacid, M., Marzouk, M. and Zhu, X. Multiview: Multi-level video content representation and retrieval. Journal of Electrical Imaging, Vol. 10, No. 4, pp. 895--908, October 2001.]]Google ScholarGoogle ScholarCross RefCross Ref
  13. Guntzer, U., Balke, W-T. and Kiessling, W. Optimizing multi-feature queries for image databases. In Proc. Of 26th Int Conf On Very Large Databases. Cairo, Egypt. pp. 419-428. September 10---14 2000.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Hammad, M., Aref, W., and Elmagarmid, A. Search-based buffer management policies for streaming in continuous media. In Proc. of the IEEE Int Conf on Multimedia and Expo. Lausanne, Switzerland. August 26---29, 2002.]]Google ScholarGoogle ScholarCross RefCross Ref
  15. Hammad, M., Franklin, M., Aref, W. and Elmagarmid. A. Scheduling for shared window joins over data streams. In Proc. of the 29th Int Conf on Very Large Data Bases. 2003.]]Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Hammad, M., Aref, W. and Elmagarmid. A. Stream Window Join: Tracking Moving Objects in Sensor-Network Databases. In Proc. of the 15th SSDBM Conf. Jul 2003.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Hellerstein, J., Naughton, J. and Pfeffer, A. Generalized search trees for database systems. In Proc. of 21st Int Conf on Very Large Data Bases. Zurich, Switzerland. September 11--15, 1995.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Ilyas, I. and Aref, W. SP-GiST: An extensible database index for supporting space partitioning trees. Journal of Intelligent System. 17(2-3). pp. 215--235. 2001.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Ilyas, I, Aref, W, and Elmagarmid, A. Joining ranked inputs in practice. In Proc. of the 28th Int Conf on Very Large Data Bases. Hong Kong, China. 2002.]]Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Ilyas, I. and Aref, W. An extensible index for spatial databases. In Proc of the 13th Int Conf on Statistical and Scientific Databases. Virginia. July 2001.]]Google ScholarGoogle Scholar
  21. Katayama, N. and Satoh, S. The SR-tree: An index structure for high dimensional nearest neighbor queries. SIGMOD Record, ACM Special Interest Group on Management of Data, 26(2). 1997.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. S. Madden, M. J. Franklin, J. M. Hellerstein and W. Hong. The design of an acquisitional query processor for sensor networks. In Proc. of the SIGMOD Conf. 2003.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Nepal, S., Ramakrishna, M. Query processing issues in image (multimedia) databases. In Proc. of the 15th Int Conf on Data Engineering. Sydney, Australia. pp. 22-29. March 23--26, 1999.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Natsev, A., Chang, Y-C., Smith, J., Li, C-S. and Vitter, J. Supporting incremental join queries on ranked inputs. In Proc. of 27th Int Conf on Very Large Data Bases. Rome, Italy. 2001.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Seshadri, P. Predator: A resource for database research. SIGMOD Record. 27(1). pp. 16--20. 1998.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. R. T. Snodgrass. Developing Time-Oriented Database Applications in SQL. Morgan Kaufmann, 2000.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Thomas, M., Carson, C., and Hellerstein, J. Creating a Customized Access Method for Blobworld, In Proc of the 16th Int Conf on Data Engineering. San Diego, CA, March 2000.]] Google ScholarGoogle ScholarDigital LibraryDigital Library

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          cover image ACM Conferences
          MMDB '03: Proceedings of the 1st ACM international workshop on Multimedia databases
          November 2003
          102 pages
          ISBN:1581137265
          DOI:10.1145/951676

          Copyright © 2003 ACM

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          • Published: 7 November 2003

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