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Design of Athlete Information Provision System Using Object Recognition

  • Seoksoo Kim
Conference paper
  • 709 Downloads
Part of the Communications in Computer and Information Science book series (CCIS, volume 195)

Abstract

The suggested athlete information provision system obtains the image of an athlete who is playing a game, through the broadcast cameras installed at several places of the stadium. The server extracts the uniform information using uniform information extraction/recognition module, out of the athlete image transmitted from the broadcast cameras. The extracted information is used to identify athlete information and league information stored in the database. the identified athlete information is transmitted to the smart phone by which the user is watching a live broadcast of the game, so that the user watches the broadcast relayed more easily. This is the athlete information provision service system using the uniform information as an object.

Keywords

Object Recognition Information Provision Provision System 

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References

  1. 1.
    Cho, J.-h., Kim, B.-h.: The Journal of Special Education: Theory and Practice 1, 535–555 (2006)Google Scholar
  2. 2.
    Lee, Y.W., et al.: The White Paper for the Ubiquitous Convergence System for the Urban Information Processing in Cheong Kye Cheon Area, Seoul Ubiquitous City Consortium Technical Report (2005)Google Scholar
  3. 3.
    Kim, J.-H., Kim, H.-C.: Information Retrieval System for Mobile Devices. Journal of the Korean Society of Marine Engineering 33(3), 569–577 (2009)CrossRefGoogle Scholar
  4. 4.
    Schilit, B.N., Theimer, M.M.: Disseminating active map information to mobile hosts. IEEE Network 8(5), 22–32 (2002)CrossRefGoogle Scholar
  5. 5.
    Jung, Y., Lee, H., Kim, J., Jun, M.: RFID Tag and Entrance Confirmation System Using Real-Time Object Extraction and Tracking. In: Korean Science Information Institute Conference, vol. 32(2) (2005)Google Scholar
  6. 6.
    Lim, K.T., Kim, H.Y.: A Study on Machine Printed Character Recognition Based on Character Type. Journal of Electronic Engineering Institute-CI 40(5), 26–39 (2003)Google Scholar
  7. 7.
    Gevers, T., Smeulders, A.W.M.: Pictoseek: Combining color and shape invariant features for image retrieval. IEEE Transactions on Image Processing 9(1), 102–119 (2002)CrossRefGoogle Scholar
  8. 8.
    Koller, D., Daniilidis, J., Nagel, H.: Model -based Object Tracking in Monocular Image Sequences of Road Traffic Sences. Int’l J. of Computer Vision 10(3), 257–281 (1993)CrossRefGoogle Scholar
  9. 9.
    Yang, J., Waibel, A.: A Real-Time Face Tracker. In: IEEE Workshop on Applications of Computer Vision, pp. 142–147 (1996)Google Scholar
  10. 10.
    Gonzalez, R.C., Woods, R.E.: Digital Image Processing, pp. 189–200. Addison-Wesley Inc., Reading (1995)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Seoksoo Kim
    • 1
  1. 1.Dept. of MultimediaHannam Univ.Daejeon-cityKorea

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