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Detection of Abnormal Event in Complex Situations Using Strong Classifier Based on BP Adaboost

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Intelligent Computing Theories and Application (ICIC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9772))

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Abstract

In order to recognize the abnormal event, such as emergency or panic, happened in public scenes timely, an algorithm based on features extraction and BP Adaboost to detect abnormal frame event from surveillance video of complex situation is proposed. The proposed method detects an abnormal event where people are running, and this panic situation is simulated by the frame in a video. Experiments show that the method can distinguish and detect the abnormal event effectively and efficiently, which has potentiality to be used in the real public monitoring.

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Acknowledgement

This work is partially supported by the ANR AutoFerm project (agence nationale de la recherche, Auto-ferme) and the Platform CAPSEC (capteurs pour la sécurité) funded by Région Champagne-Ardenne and FEDER (fonds européen de développement régional), the Fundamental Research Funds for the Central Universities and the National Natural Science Foundation of China (Grant No. U1435220, 61503017, 61365003), Gansu Province Basic Research Innovation Group Project (1506RJIA031).

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Authors and Affiliations

  1. School of Automation Science and Electrical Engineering, Beihang University, Beijing, 100191, China

    Yuqi Zhang, Tian Wang & Meina Qiao

  2. Institute Charles Delaunay-LM2S-UMR STMR 6279 CNRS, University of Technology of Troyes, 10004, Troyes, France

    Aichun Zhu & Hichem Snoussi

  3. College of Electrical and Information Engineering, Lanzhou University of Technology, No. 287, Langongping Road, Lanzhou, 730050, Gansu, China

    Ce Li

Authors
  1. Yuqi Zhang
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  2. Tian Wang
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  3. Meina Qiao
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  4. Aichun Zhu
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  5. Ce Li
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  6. Hichem Snoussi
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Corresponding author

Correspondence to Tian Wang .

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Editors and Affiliations

  1. Tongji University , Shanghai, China

    De-Shuang Huang

  2. University of Ulsan , Ulsan, Korea (Republic of)

    Kang-Hyun Jo

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Zhang, Y., Wang, T., Qiao, M., Zhu, A., Li, C., Snoussi, H. (2016). Detection of Abnormal Event in Complex Situations Using Strong Classifier Based on BP Adaboost. In: Huang, DS., Jo, KH. (eds) Intelligent Computing Theories and Application. ICIC 2016. Lecture Notes in Computer Science(), vol 9772. Springer, Cham. https://doi.org/10.1007/978-3-319-42294-7_21

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  • DOI: https://doi.org/10.1007/978-3-319-42294-7_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42293-0

  • Online ISBN: 978-3-319-42294-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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