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Loitering Detection Using Bayesian Appearance Tracker and List of Visitors

  • Conference paper
Advances in Multimedia Information Processing - PCM 2008 (PCM 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5353))

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Abstract

This paper presents a framework of detecting loitering pedestrians in a video surveillance system. When a pedestrian appears in the field of view of the monitoring camera, he/she is tracked by a Bayesian appearance tracker (BAT). The tracker takes the advantage of Bayesian decision to associate the detected pedestrians according to their color appearances among consecutive frames. The pedestrian’s appearance is modeled as a multivariate normal distribution and recorded in a table called list of visitors (LV). LV also records time stamps when the pedestrian appears as an appearing history. Therefore, even though the pedestrian leaves and returns to the scene, he/she can still be recognized and re-identified as a locally or globally loitering suspect by using different rules. A 10-minute video about three loitering pedestrians is used to test the proposed system. They are successfully detected and recognized from other passing-by pedestrians.

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References

  1. Bird, N.D., Masoud, O., Paapnikolopoulos, P.P., Isaacs, A.: Detection of Loitering Individuals in Public Transportation Areas. IEEE Trans. Intelligent Transportation Systems 6(2), 167–177 (2005)

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Author information

Authors and Affiliations

  1. Industrial Technology Research Institute, Hsinchiu, Taiwan

    Chung-Hsien Huang, Ming-Yu Shih, Yi-Ta Wu & Jau-Hong Kao

Authors
  1. Chung-Hsien Huang
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  2. Ming-Yu Shih
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  3. Yi-Ta Wu
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  4. Jau-Hong Kao
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Editor information

Editors and Affiliations

  1. Department of Engineering Science, National Cheng Kung University, No.1, University Road, 701, Tainan City, Taiwan

    Yueh-Min Ray Huang

  2. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 95, Zhongguancun East Road, 100190, Beijing, China

    Changsheng Xu

  3. Institute of Biomedical Engineering, National Cheng Kung University, No. 1, University Road, 701, Tainan City, Taiwan

    Kuo-Sheng Cheng

  4. Department of Electrical Engineering, National Cheng Kung University, No. 1, University Road, 701, Tainan City, Taiwan

    Jar-Ferr Kevin Yang

  5. Department of Electrical and Computer Engineering, Concordia University, S-EV005.139, 1515 St. Catherine West, Montreal, H4G 2W1, Quebec, Canada

    M. N. S. Swamy

  6. Microsoft Research Asia, 5/F, Beijing Sigma Center, No. 49, Zhichun Road, Hai Dian District, 100080, Beijing, China

    Shipeng Li

  7. Department of Information Management, National Kaohsiung University of Applied Sciences, No. 415, Jiangong Road, Sanmin District, 80778, Kaohsiung, Taiwan

    Jen-Wen Ding

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© 2008 Springer-Verlag Berlin Heidelberg

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Huang, CH., Shih, MY., Wu, YT., Kao, JH. (2008). Loitering Detection Using Bayesian Appearance Tracker and List of Visitors. In: Huang, YM.R., et al. Advances in Multimedia Information Processing - PCM 2008. PCM 2008. Lecture Notes in Computer Science, vol 5353. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89796-5_111

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  • DOI: https://doi.org/10.1007/978-3-540-89796-5_111

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89795-8

  • Online ISBN: 978-3-540-89796-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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