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A Method for Online Analysis of Structured Processes Using Bayesian Filters and Echo State Networks

  • Dimitrios I. Kosmopoulos
  • Fillia Makedon
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7585)

Abstract

We propose a Bayesian filtering framework for online analysis of visual structured processes, which can be combined with the Echo State Network (ESN) to capture prior information. With the proposed method we mitigate the effective Markovian Behavior of the ESN. We are able to keep a set of hypotheses about the entire history of behaviors and to evaluate them online based on new observations. The performance is evaluated under two complex visual behavior understanding scenarios using public datasets: a visual process for a kitchen table preparation and a real life manufacturing process.

Keywords

Hide Markov Model Gaussian Mixture Model Zernike Moment Online Analysis Task Duration 
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

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Dimitrios I. Kosmopoulos
    • 1
  • Fillia Makedon
    • 1
  1. 1.Computer Science and EngineeringUniversity of Texas at ArlingtonUSA

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