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Kinect Sensing of Shopping Related Actions

  • Mirela Popa
  • Alper Kemal Koc
  • Leon J. M. Rothkrantz
  • Caifeng Shan
  • Pascal Wiggers
Part of the Communications in Computer and Information Science book series (CCIS, volume 277)

Abstract

Surveillance systems in shopping malls or supermarkets are usually used for detecting abnormal behavior. We used the distributed video cameras system to design digital shopping assistants which assess the behavior of customers while shopping, detect when they need assistance, and offer their support in case there is a selling opportunity.  In this paper we propose a system for analyzing human behavior patterns related to products interaction, such as browse through a set of products, examine, pick products, try on, interact with the shopping cart, and look for support by waiving one hand.  We used the Kinect sensor to detect the silhouettes of people and extracted discriminative features for basic action detection. Next we analyzed different classification methods, statistical and also spatio-temporal ones, which capture relations between frames, features, and basic actions. By employing feature level fusion of appearance and movement information we obtained an accuracy of 80% for the mentioned six basic actions.

Keywords

Shopping Behavior Action Recognition Surveillance Kinect 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Mirela Popa
    • 1
    • 2
  • Alper Kemal Koc
    • 1
    • 2
  • Leon J. M. Rothkrantz
    • 1
    • 3
  • Caifeng Shan
    • 2
  • Pascal Wiggers
    • 1
  1. 1.Man-Machine Interaction group, Department of MediamaticsDelft University of TechnologyDelftThe Netherlands
  2. 2.Video and Image Processing Department, Philips Research, HTC 36EindhovenThe Netherlands
  3. 3.Sensor Technology, SEWACO DepartmentNetherlands Defence AcademyDen HelderThe Netherlands

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