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Fast Motion Detection Based on Accumulative Optical Flow and Double Background Model

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Computational Intelligence and Security (CIS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3802))

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Abstract

Optical flow and background subtraction are important methods for detecting motion in video sequences. This paper integrates the advantages of these two methods. Firstly, proposes a high precise algorithm for optical flow computation with analytic wavelet and M-estimator to solve the optical flow restricted equations. Secondly, introduces the extended accumulative optical flow and also provides its computational strategies, then obtains a robust motion detection algorithm. Furthermore, combines a background subtraction algorithm based on the double background model with the extended accumulative optical flow to give an abnormity alarm in time. All obvious proofs of experiments show that, our algorithm can precisely detect moving objects, no matter slow or little, preferably solve the occlusions as well as give an alarm fast.

This work is supported by the NSFC(63075013), the Huo Ying Dong Education Foundation (81095).

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References

  1. Iketani, A., Kuno, Y., Shimada, N.: Real time Surveillance System Detecting Persons in Complex Scenes. Proceedings of Image Analysis and Processing, 1112–1115 (1999)

    Google Scholar 

  2. Ong, E.P., Spann, M.: Robust Multi-resolution Computation of Optical Flow. In: Acoustics, Speech and Signal Proceedings 1996 (ICASSP 1996), pp. 1938–1941 (1996)

    Google Scholar 

  3. Suhling, M., Arigovindan, M., Hunziker, P., Unser, M.: Multi-resolution moment filters: theory and applications. IEEE Transactions Image Processing 13(4), 484–495 (2004)

    Article  MathSciNet  Google Scholar 

  4. Bernard, C.P.: Discrete Wavelet Analysis for Fast Optic flow Computation. PhD Dissertation, Ecole polytechnique (1999)

    Google Scholar 

  5. Wixson, L.: Detecting Salient Motion by Accumulating Directionally-Consistent Flow. IEEE Transactions on Pattern Analysis And Machine Intelligence 22(8), 744–780 (2000)

    Article  Google Scholar 

  6. Barron, J., Fleet, D., Beauchemin, S.: Performance of Optical Flow Techniques. International Journal of Computer Vision 12(1), 42–77 (1994)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Digital Media Lab, School of Computer Science & Engineering, Beihang University, Beijing, China

    Jin Zheng, Bo Li, Bing Zhou & Wei Li

Authors
  1. Jin Zheng
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  2. Bo Li
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  3. Bing Zhou
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  4. Wei Li
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Editor information

Editors and Affiliations

  1. Microelectronic Instiute, Xidian University, 710071, Xi’an, China

    Yue Hao

  2. Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong

    Jiming Liu

  3. School of Computer Science and Technology, Xidian University, Xi’an, China

    Yu-Ping Wang

  4. Department of Computer Science, Hong Kong Baptist University, Hong Kong,  

    Yiu-ming Cheung

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

  6. Life Science Research Center, School of Electronic Engineering, Xidian University, 710071, Xi’an, Shaanxi, China

    Licheng Jiao

  7. Key Laboratory of Computer Networks and Information Security(Ministry of Education), Xidian University, 710071, Xi’an, China

    Jianfeng Ma

  8. National Laboratory of Antennas and Microwave Technology, Xidian University, 710071, Xi’an, Shanxi, P.R. China

    Yong-Chang Jiao

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© 2005 Springer-Verlag Berlin Heidelberg

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Zheng, J., Li, B., Zhou, B., Li, W. (2005). Fast Motion Detection Based on Accumulative Optical Flow and Double Background Model. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3802. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596981_43

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  • DOI: https://doi.org/10.1007/11596981_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30819-5

  • Online ISBN: 978-3-540-31598-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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