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A Formal Fuzzy Framework for Representation and Recognition of Human Activities

  • Suphot Chunwiphat
  • Patrick Reignier
  • Augustin Lux
Part of the IFIP International Federation for Information Processing book series (IFIPAICT, volume 296)

Abstract

This paper focuses on the problem of human activity representation and automatic recognition. We first describe an approach for human activity representation. We define the concepts of roles, relations, situations and temporal graph of situations (the context model). This context model is transformed into a Fuzzy Petri Net which naturally expresses the smooth changes of activity states from one state to another with gradual and continuous membership functions. Afterward, we present an algorithm for recognizing human activities observed in a scene. The recognition algorithm is a hierarchical fusion model based on fuzzy measures and fuzzy integrals. The fusion process nonlinearly combines events, produced by an activity representation model, based on an assumption that all occurred events support the appearance of a modeled scenario. The goal is to determine, from an observed sequence, the confidence factor that each modeled scenario (predefined in a library) is indeed describing this sequence. We have successfully evaluated our approach on the video sequences taken from the European CAVIAR project1.

Keywords

Activity Recognition Context Model Fuzzy Measure Transition Firing Fuzzy Condition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© IFIP International Federation for Information Processing 2009

Authors and Affiliations

  • Suphot Chunwiphat
    • 1
  • Patrick Reignier
    • 2
  • Augustin Lux
    • 2
  1. 1.Department of Electronic Engineering Technology, College of Industrial TechnologyKing Mongkut's University of Technology North BangkokBangsueThailand
  2. 2.LIG — PRIMA — INRIA Rhône-AlpesSaint Ismier cedexFrance

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