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Multimedia Tools and Applications

, Volume 24, Issue 2, pp 89–103 | Cite as

A Multimedia Information Repository for Cross Cultural Dance Studies

  • Forouzan Golshani
  • Pegge Vissicaro
  • Youngchoon Park
Article

Abstract

Multimedia technologies provide effective means for studying the evolution of dance across time and space. The study may be at the micro level which analyzes the development of an individual's performance and the movements of the dancer(s) in 3D space and over the length of the dance. However, at the macro level, diffusion of dance throughout the world over a span of time may be investigated in order to trace particular dance repertoires that may have traveled across various cultures and traditions. Although clearly different with respect to the expected objectives, both micro level analysis and macro level analysis require detailed comparison of patterns on the basis of certain characteristics that are deemed significant for a given dance. These characteristics are diverse in nature and may include such parameters as design formations, use of space (including level, direction, etc.), dynamics, paraphernalia (e.g., swords, sticks, etc.), sound, and color.

We present the design of a multimedia information system with two complimentary aims. The first is to automate, to the greatest degree possible, the process of comparison and analysis of dance and human movement. Much of the information about dance exists in the form of video, images, audio and written commentaries, all collected into a digital library. As dance related materials are added, a wide variety of routines are needed to extract the necessary low level features from the multimedia objects. These low level features are then interpreted to human understandable features and patterns, which will be used for analysis by specialists. The second aim is to bring artists and technologists closer in a meaningful way.

multimedia information systems dance studies multimedia content analysis 

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References

  1. 1.
    G.R. Bradski, "Computer video face tracking for use in a perceptual user interface," in Intel Technology Journal Q2'98.Google Scholar
  2. 2.
    B. Feiten and S. Günzel, "Automatic indexing of a sound database using self-organizing neural nets," Computer Music Journal, Vol. 18, No. 3, pp. 53–65, 1994.Google Scholar
  3. 3.
    F. Golshani and P. Vissicaro, "Design of a multi-ethnic dance information repository," in Proc. of Workshop on Multimedia Semantics, Milovy, Czech Republic, Nov. 2002, pp. 76–86.Google Scholar
  4. 4.
    Hirata and T. Kato, "Rough sketch-based image information retrieval," NEC Research and Development, Vol. 34, No. 2, pp. 263–273, 1993.Google Scholar
  5. 5.
    T. Horprasert, D. Harwood, and L. Davis, "A statistical approach for real time robust background subtraction and shadow detection," in Proc. of IEEE Frame Rate Workshop, 1999.Google Scholar
  6. 6.
    K. Kohol, "Gesture segmentation in complex motion sequences," MS thesis, Computer Science and Engineering, Arizona State University, 2003.Google Scholar
  7. 7.
    B.S. Manjunath and W.Y. Ma, "Texture features for browsing and retrieval of image data," IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 18, No. 8, pp. 837–841, 1996.Google Scholar
  8. 8.
    Y. Park, "A Framework for description, sharing and retrieval of semantic visual information," PhD Dissertation, Arizona State University, Computer Science, 2002.Google Scholar
  9. 9.
    Y. Park, Tutorial and Programmer's Guide of Active Video Analysis SDK, http://www.mpeg7tv.com/ pub/avasdk.pdf, 2003.Google Scholar
  10. 10.
    M.J. Swain and D.H. Ballard, "Color indexing," International Journal of Computer Vision, Vol. 7, No. 1, pp. 11–32, 1991.Google Scholar
  11. 11.
    D. Tegolo, "Shape analysis for image retrieval," SPIE Proceedings: Storage and Retrieval for Image and Video Databases II, Vol. 2185, pp. 59–69, 1994.Google Scholar
  12. 12.
    E. Wold, T. Blum, D. Keislar, and J. Wheaton, "Content-based classification, search and retrieval of audio," IEEE Multimedia, Vol. 3, No. 3, pp. 27–36, 1996.Google Scholar

Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • Forouzan Golshani
    • 1
  • Pegge Vissicaro
    • 2
  • Youngchoon Park
    • 3
  1. 1.Computer Science and EngineeringWright State UniversityDaytonUSA
  2. 2.Department of DanceArizona State UniversityTempeUSA
  3. 3.Johnson Controls, Inc.MilwaukeeUSA

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