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International Conference on Intelligent Robotics and Applications

ICIRA 2017: Intelligent Robotics and Applications pp 671–682Cite as

Statistical Abnormal Crowd Behavior Detection and Simulation for Real-Time Applications

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10463))

Abstract

This paper proposes a low computational cost method for abnormal crowd behavior detection with surveillance applications in fixed cameras. Our proposal is based on statistical modelling of moved pixels density. For modelling we take as reference datasets available in the literature focused in crowd behavior. During anomalous events we capture data to replicate abnormal crowd behavior for computer graphics and virtual reality applications. Our algorithm performance is compared with other proposals in the literature applied in two datasets. In addition, we test the execution time to validate its usage in real-time. In the results we obtain fast execution time of the algorithm and robustness in its performance.

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Acknowledgement

This work is part of the project Perception and localization system for autonomous navigation of rotor micro aerial vehicle in gps-denied environments, VisualNavDrone, 2016-PIC-024, from the Universidad de las Fuerzas Armadas ESPE, directed by Dr. Wilbert G. Aguilar.

Author information

Authors and Affiliations

  1. Dep. DECEM, Universidad de las Fuerzas Armadas ESPE, Sangolquí, Ecuador

    Wilbert G. Aguilar, Hugo Ruiz & Humberto Parra

  2. Dep. DEEE, Universidad de las Fuerzas Armadas ESPE, Sangolquí, Ecuador

    Marco A. Luna & Julio F. Moya

  3. Dep. Tierra y Construcción, Universidad de las Fuerzas Armadas ESPE, Sangolquí, Ecuador

    Marco P. Luna

  4. CICTE Research Center, Universidad de las Fuerzas Armadas ESPE, Sangolquí, Ecuador

    Wilbert G. Aguilar

  5. GREC Research Group, Universitat Politècnica de Catalunya, Barcelona, Spain

    Wilbert G. Aguilar

  6. Universitat de Barcelona, Barcelona, Spain

    Vanessa Abad

  7. PLM Research Center, Purdue University, Indiana, USA

    Marco P. Luna & Humberto Parra

  8. Universidad Politécnica de Madrid, Madrid, Spain

    Hugo Ruiz

Authors
  1. Wilbert G. Aguilar
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  2. Marco A. Luna
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  3. Hugo Ruiz
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  4. Julio F. Moya
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  5. Marco P. Luna
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  6. Vanessa Abad
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  7. Humberto Parra
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Corresponding author

Correspondence to Wilbert G. Aguilar .

Editor information

Editors and Affiliations

  1. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China

    YongAn Huang

  2. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China

    Hao Wu

  3. Institute of Industrial Research, University of Portsmouth, Portsmouth, United Kingdom

    Honghai Liu

  4. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China

    Zhouping Yin

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Aguilar, W.G. et al. (2017). Statistical Abnormal Crowd Behavior Detection and Simulation for Real-Time Applications. In: Huang, Y., Wu, H., Liu, H., Yin, Z. (eds) Intelligent Robotics and Applications. ICIRA 2017. Lecture Notes in Computer Science(), vol 10463. Springer, Cham. https://doi.org/10.1007/978-3-319-65292-4_58

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  • DOI: https://doi.org/10.1007/978-3-319-65292-4_58

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65291-7

  • Online ISBN: 978-3-319-65292-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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