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Advances in Parallel and Distributed Computing and Ubiquitous Services pp 137–143Cite as

Flexible Multi-level Regression Model for Prediction of Pedestrian Abnormal Behavior

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Part of the Lecture Notes in Electrical Engineering book series (LNEE,volume 368)

Abstract

The high incidence of heinous crime is increasing to use of CCTV. However, CCTV has been used to obtain evidence rather than crime prevention. Also it shows a weak effect about preventing crime. To solve the weak effort, we propose a Flexible Multi-level Regression (FMR) model that should estimate a dangerous situation for the pedestrian. The FMR model is tracking the behavior of between pedestrians from multiple CCTV that are located in different locations. The FMR has a prediction logic that should estimate an abnormal situation to analyze the possibility of crime by using the Regression and Apriori algorithm. The FMR model can be usefully used to prevent the crime because of an immediate response and rapid situation assessment.

Keywords

  • CCTV systems
  • Flexible multi-level regression
  • Behavior prediction
  • Abnormal behavior
  • Situation assessment

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  • DOI: 10.1007/978-981-10-0068-3_17
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Acknowledgements

This work was supported by Institute for Information and communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (B0101-15-1282-00010002, Suspicious pedestrian tracking using multiple fixed cameras).

Author information

Authors and Affiliations

  1. Department of Multimedia Science, SookMyung Women’s University, Seoul, Korea

    Yu-Jin Jung & Yong-Ik Yoon

Authors
  1. Yu-Jin Jung
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  2. Yong-Ik Yoon
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Corresponding author

Correspondence to Yong-Ik Yoon .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engg., Seoul University of Science & Technology, Seoul, Korea (Republic of)

    James J. (Jong Hyuk) Park

  2. Computer Science & Engineering, Gangneung-Wonju National University, Wonju, Korea (Republic of)

    Gangman Yi

  3. Multimedia Engineering, Dongguk University, Seoul, Korea (Republic of)

    Young-Sik Jeong

  4. School of Computer Science, University of Adelaide, ADELAIDE, South Australia, Australia

    Hong Shen

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© 2016 Springer Science+Business Media Singapore

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Jung, YJ., Yoon, YI. (2016). Flexible Multi-level Regression Model for Prediction of Pedestrian Abnormal Behavior. In: Park, J., Yi, G., Jeong, YS., Shen, H. (eds) Advances in Parallel and Distributed Computing and Ubiquitous Services. Lecture Notes in Electrical Engineering, vol 368. Springer, Singapore. https://doi.org/10.1007/978-981-10-0068-3_17

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  • DOI: https://doi.org/10.1007/978-981-10-0068-3_17

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-0067-6

  • Online ISBN: 978-981-10-0068-3

  • eBook Packages: Computer ScienceComputer Science (R0)