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@ARTICLE{Smith_IEEE-PAMI_2008,
         author = {Smith, Kevin C. and Ba, Sil{\`{e}}ye O. and Odobez, Jean-Marc and Gatica-Perez, Daniel},
       projects = {Idiap, CARETAKER, IM2},
          title = {Tracking the visual focus of attention for a varying number of
  wandering people},
        journal = {IEEE Trans. on Pattern Analysis and Machine Intelligence},
         volume = {30},
         number = {7},
           year = {2008},
       abstract = {In this article, we define and address the problem of finding the visual focus of attention 
for a varying number of wandering people (VFOA-W) -- determining where a person is
looking when their movement is unconstrained. 
  VFOA-W estimation is a new and important
  problem with implications in behavior understanding and
  cognitive science, as well as real-world applications.  One such
  application, presented in this article, monitors the
  attention passers-by pay to an outdoor advertisement using a single video camera.  
  In our
  approach to the VFOA-W problem, we propose a multi-person tracking
  solution based on a dynamic Bayesian network that
  simultaneously infers the number of people in a scene, their body
  locations, their head locations, and their head pose.  
  For efficient inference in the resulting
  variable-dimensional state-space we propose a Reversible Jump Markov
  Chain Monte Carlo (RJMCMC) sampling scheme, as well as a novel global observation
  model which determines the number of people in the scene and their locations.
  To determine if a person is looking at the advertisement or not, we 
  propose a Gaussian Mixture Model (GMM) and Hidden Markov Model (HMM)-based 
  VFOA-W model which uses head pose and
  location information.
  Our models are evaluated for tracking performance and ability to recognize
  people looking at an outdoor advertisement, with results indicating
  good performance on sequences where up to three people pass in
  front of an advertisement.},
            pdf = {https://publications.idiap.ch/attachments/papers/2008/Smith_IEEE-PAMI_2008.pdf}
}