Abstract
Video data management is fast becoming one of the most important topics in multimedia databases. In this paper, we describe the development of an experimental video information management system, called “VIMS”, being implemented at the Hong Kong University of Science & Technology, which employs two fundamental components—i) a video Classification Component (VCC) for the generation of effective indices necessary for structuring the video data, and ii) a Conceptual Clustering Mechanism (CCM) having extended object-oriented features and techniques. By incorporating CCM concepts and techniques together with the classified features and indices generated from the VCC, the information management system enables users to form dynamically, among other things, video programs (or segments) from existing objects based on semantic features/index terms. A prototype of this system has been constructed, using a persistent object storage manager (viz., EOS), on Sun4 workstations.
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References
T. Arndt, “A survey of recent research in image database management,” in Proc. IEEE Workshop on Visual Languages (Cat. No. 90TH0330-1), 1990, pp. 92–97.
A. Bimbo, E. Vicario, and D. Zingoni, “Sequence retrieval by contents through spatio temporal indexing,” in Proc. IEEE Symposium on Visual Language (Cat. No. 93TH0562-9), 1993, pp. 88–92.
EOS, EOS 2.1 User’s Manual, Tech. Rep., AT&T Bell Lab., Murray Hill: New Jersey 07974, U.S.A., 1994.
C.W. Fung and Q. Li, “Versatile querying facilities for a dynamic object clustering model,” in Proceedings of OOER’95: Object-Oriented and Entity-Relationship Modeling, 14th International Conference, Gold Coast, Australia, Dec. 13–15, 1995, pp. 77–88.
W. Grosky, F. Fotouli, I. Sethi, and B. Capatina, “Object-oriented databases: Definition and research directions,” ACM SIGMOD Record, Vol. 23, 1994.
K. Hirata and T. Kato, “Query by visual example,” in Advances in Database Technology EDBT’92 (Proc. of Third International Conference on Extending Database Technology), A. Pirotte, C. Delobel, and G. Gottlob (Eds.), Lecture Notes in Computer Science, Vienna, Austria, Springer-Verlag: Vol. 580, pp. 56–71, March 1992.
L.S. Huang, J.C.M. Lee, Q. Li, and W. Xiong, “An experimental video database management system based on advanced object-oriented techniques,” in Proceedings of the SPIE—The International Society for Optical Engineering, Vol. 2670, pp. 158–169, 1996.
R. Jain and A. Hampapur, “Metadata in video databases,” SIGMOD Record, Vol. 23, pp. 27–33, 1994.
T. Kato, “Database architecture for content-based image retrieval,” in SPIE Proc. Image Storage and Retrieval Systems, Vol. 1662, pp. 112–123, 1992.
J.C.M. Lee and M.C. Ip, “A robust approach for camera break detection in color video sequence,” in Proc. IAPR Workshop on Machine Vision Application (MVA’94), Kawasaki, Japan, Dec. 1994, pp. 502–505.
J.C.M. Lee, W. Xiong, D.G. Shen, and R.H. Ma, “Video segment indexing through classification and interactive view-based query,” in Proceedings of Second Asian Conference on Computer Vision, Singapore, Dec. 1995, Vol. 2, pp. 524–528.
Q. Li and J. Smith, “A conceptual model for dynamic clustering in object databases,” in Proc. 18th Intl. Conf. on VLDB, 1992, pp. 457–468.
Q. Li and J.C.M. Lee, “Dynamic object clustering for video database manipulations,” in Proc. IFIP 2.6 Working Conference on Visual Database Systems, Lausanne, Switzerland, March 1995, pp. 125–137.
T.D.C. Little, E. Ahanger, R.J. Folz, J.F. Gibbon, F.W. Reeve, D.H. Schelleng, and D. Venkatesh, “A digital on-demand video service supporting content-based queries,” in Proc. First ACM Intl. Conf. on Multimedia, 1993, pp. 427–436.
A. Nagasaka and Y. Tanaka, “Automatic video indexing and full-video search for object appearances,” in IFIP Proc. Visual Database Systems, II, E. Knuth and L. Wegner (Eds.), IFIP, Elsevier Science Publishers B.V.: (North-Holland), 1992, pp. 113–127.
A. Nagasaka, T. Miyatake, and H. Ueda, “Video retrieval method using a sequence of representative images in a scene,” in Proceedings of IAPR Workshop on Machine Vision Applications, Kawasaki, Japan, Dec. 1994, pp. 79–82.
W. Niblack, R. Barber, W. Equitz, M. Flickner, E. Glasman, D. Petkovic, P. Yanker, C. Faloutsos, and G. Taubin, “The QBIC project: Query images by content using color, texture and shape,” in SPIE Proc. Storage and retrieval for image and video databases, 1993, Vol. 1908, pp. 173–186.
E. Oomoto and K. Tanaka, “Ovid: Design and implementation of a video-object database system,” IEEE Trans. on Knowledge and Data Engineering, Vol. 5, pp. 629–643, 1994.
A. Pentland, R.W. Picard, and S. Scaroff, “Photobook: Tools for content-based manipulation of image databases,” in SPIE Proc. Storage and retrieval for image and video databases II, 1994, Vol. 2185, pp. 34–46. “Longer version available as MIT Media Lab Perceptual Computing,” Technical Report No. 255, Nov. 1993.
S.W. Smoliar and H.J. Zhang, “Content-based video indexing and retrieval,” IEEE Multimedia, Vol. 1, pp. 356–365, 1994.
Y. Tonomura, “Video handling based one structured information for hypermedia systems,” in Proc. ACM Int’l Conf. on Multimedia Information Systems, New York, USA, ACM Press, 1991, pp. 333–344.
H. Ueda, T. Miyataka, and S. Yoshizawa, “IMPACT: An interactive natural-motion-picture dedicated multimedia authoring system,” Proc. Human Factors in Compating Systems CHI’91, 1991, pp. 343–350.
K.W.E. Bertino, and J.F. Garza, “Composite object revisited,” in Proc. of ACM SIGMOD Intl. Conf. on Management of Data, 1989, pp. 337–347.
W. Xiong, J.C.M. Lee, and M.C. Ip, “Net comparison: A fast and effective method for classifying image sequences,” in Proceedings of the SPIE—The International Society for Optical Engineering, San Jose, CA, USA, Feb. 1995, Vol. 2420, pp. 318–28. Storage and Retrieval for Image and Video Database III.
W. Xiong, J.C.M. Lee, and R.H. Ma, “Automatic video data structuring through shot partitioning and key frame selection,” Machine Vision and Application: Special issue on Storage and Retrieval for Still Image and Video Databases (1996), (submitted), (Technical Report HKUST-(’S96-13).
M. Yeung, B.L. Yeo, W. Wolf, and B. Liu, “Video browsing using clustering and scene transitions on compressed sequences,” in Conf. on Multimedia Computing and Networking, Vol. 2417, 1995, Proceedings of the SPIE—The International Society for Optical Engineering, 1995, pp. 399–413.
H.J. Zhang, A. Kankanhalli, and S.W. Smoliar, “Automatic partitioning of full-motion video,” ACM Multimedia Systems, Vol. 1, pp. 10–28, 1993.
H.J. Zhang, C.Y. Low, Y.H. Gong, and S.W. Smoliar, “Video parsing using compressed data,” in Proceedings of the SPIE—The International Society for Optical Engineering, San Jose, CA, USA, Feb. 7–9, 1994, Vol. 2182, pp. 142–149. Image and Video Processing II.
H.J. Zhang and S.W. Smoliar, “Developing power tools for video indexing and retrieval,” in SPIE Proc. Storage and retrieval for image and video databases II, 1994, Vol. 2185, pp. 140–149.
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Lee, J.CM., Li, Q., Xiong, W. (1997). VIMS: A Video Information Management System. In: Zhang, H.J., Aigrain, P., Petkovic, D. (eds) Representation and Retrieval of Video Data in Multimedia Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-585-31786-1_2
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DOI: https://doi.org/10.1007/978-0-585-31786-1_2
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