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Movement Detection and Tracking Using Video Frames

  • Josue Hernandez
  • Hiroshi Morita
  • Mariko Nakano-Miytake
  • Hector Perez-Meana
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5856)

Abstract

The use of image processing schemes as part of the security systems have been increasing, to detect, classify as well as to tract object and human motion with a high precision. To this end several approaches have been proposed during the last decades using image processing techniques, because computer vision let us to manipulated digital image sequences to extract useful information contained in a video stream. In this paper we present a motion detection algorithm using the movement vectors estimation which are subsequently filtered to obtain better information about real motion into a given scenes. Experimental results show that the accuracy of proposed system.

Keywords

Motion Vectors Movement Detection Surveillance System Surveillance system development 

References

  1. 1.
    Jones, B.T.: Low-Cost Outdoor Video Motion and Non-Motion Detection. Processing of Security Technology, 376–380 (1995)Google Scholar
  2. 2.
    Paladino, V.: Introduction of Video Compression Under the Standard MPEG-2. The Institute of Electronic Engineer,Spain, 3–24 (2005)Google Scholar
  3. 3.
    Richardson, I.E.: H.264 and MPEG-4 Video Compression, Video Coding for the Next-Generation Multimedia, pp. 27–41. Wiley, UK (2004)Google Scholar
  4. 4.
    Watkinson, J.: The MPEG Handbook: MPEG-1, MPEG-2, MPEG-4. Focal Press (2001)Google Scholar
  5. 5.
    Tudor, P.N.: MPEG-2 Video Compression: Tutorial. Journal of Electronics and Communication Engineering, 1-5 (December 1995)Google Scholar
  6. 6.
    Zhang, Z.: Mining Surveillance Video for Independent Motion Detection. In: IEEE Internacional Conference on Data Mining, pp. 741–744 (2005)Google Scholar
  7. 7.
    Favalli, L., Mecocci, A., Moschetti, F.: Object Tracking For Retrieval in MPEG2. IEEE, Trans. on Circuit and Syst. for Video Technology, 427–432 (2000)Google Scholar
  8. 8.
    Hariharakrishnan, K., Schonfeld, D., Raffy, P., Yassa, F.: Video Tracking Using Block Matching. In: IEEE, International Conference on Image Processing, pp. 945–948 (2003)Google Scholar
  9. 9.
    Yoneyama, A., Nakajima, Y., Yanagihara, H., Sugano, M.: Moving Object Detection from MPEG Video Stream. Systems and Computers in Japan 30(13), 1–11 (1999)CrossRefGoogle Scholar
  10. 10.
    Avidan, S.: Support Vector Tracking. IEEE 26(8), 1064–1071 (2004)Google Scholar
  11. 11.
    Nguyen, H., Smeulders, A.: Fast Occluded Object Tracking by a Robust Appearance Filter. IEEE Trans. on Image Processing 26(8), 1099–1103 (2004)Google Scholar
  12. 12.
    Lin, M., Tomasi, C.: Surfaces with Occlusions from Layered Stereo. IEEE 26(8), 1073–1098 (2004)Google Scholar
  13. 13.
    Sebastian, T., Klein, P., Kimia, B.: Recognition of Shapes by Editing Their Sock Graphs. IEEE Trans. on Image Processing 26(5), 550–554 (2004)Google Scholar
  14. 14.
    Coding Audiovisual Objects Part 2, International Standard Organization / Int. Electronics Communications (ISO/IEC), 14496Google Scholar
  15. 15.
    Hernández García, J., Pérez-Meana, H., Nakano Miyatake, M.: Video Motion Detection using the Algorithm of Discrimination and Hamming Distance. In: Ramos, F.F., Larios Rosillo, V., Unger, H. (eds.) ISSADS 2005. LNCS, vol. 3563, pp. 321–330. Springer, Heidelberg (2005)Google Scholar
  16. 16.
    Gryn, J.M., Wlides, R., Tsotsos, J.K.: Detecting Motion Patterns via Directional Maps with Applications to Surveillance. Computer Vision and Image Understanding 113, 291–307 (2009)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Josue Hernandez
    • 1
  • Hiroshi Morita
    • 2
  • Mariko Nakano-Miytake
    • 1
  • Hector Perez-Meana
    • 1
  1. 1.National Polytechnic InstituteMexicoMexico
  2. 2.The University of Electro-CommunicationsTokyoJapan

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