Towards Automated Models of Activities of Daily Life (bibtex)
by Michael Beetz, Jan Bandouch, Dominik Jain and Moritz Tenorth
Abstract:
We propose automated probabilistic models of everyday activities (AM-EvA) as a novel technical means for the perception, interpretation, and analysis of everyday manipulation tasks and activities of daily life. AM-EvAs are based on action-related concepts in everyday activities such as action-related places (the place where cups are taken from the cupboard), capabilities (the objects that can be picked up single-handedly), etc. These concepts are probabilistically derived from a set of previous activities that are fully and automatically observed by computer vision and additional sensor systems. AM-EvA models enable robots and technical systems to analyze activities in the complete situation and activity context. They render the classification and the assessment of actions and situations objective and can justify the probabilistic interpretation with respect to the activities the concepts have been learned from. In this paper, we describe the current state of implementation of the system that realizes this idea of automated models of everyday activities and show example results from the observation and analysis of table setting episodes.
Reference:
Michael Beetz, Jan Bandouch, Dominik Jain and Moritz Tenorth, "Towards Automated Models of Activities of Daily Life", In First International Symposium on Quality of Life Technology – Intelligent Systems for Better Living, Pittsburgh, Pennsylvania USA, 2009.
Bibtex Entry:
@InProceedings{beetz09qlts,
  author =       {Michael Beetz and Jan Bandouch and Dominik Jain and Moritz Tenorth},
  title =        {{Towards Automated Models of Activities of Daily Life}},
  booktitle =    {First International Symposium on Quality of Life Technology -- Intelligent Systems for Better Living},
  year =         {2009},
  address =      {Pittsburgh, Pennsylvania USA},
  url = {https://ai.uni-bremen.de/papers/beetz09qlts.pdf},
  bib2html_pubtype ={Conference Paper},
  bib2html_rescat  = {Learning,Models,Planning,Perception,Knowledge,Reasoning,Representation},
  bib2html_groups = {Memoman,K4C,ProbCog},
  bib2html_funding = {CoTeSys},
  bib2html_domain  = {Assistive Household},
  abstract =     {We propose automated probabilistic models of everyday
  activities (AM-EvA) as a novel technical means for the
  perception, interpretation, and analysis of everyday manipulation
  tasks and activities of daily life. AM-EvAs are based on
  action-related concepts in everyday activities such as
  action-related places (the place where cups are taken from the
  cupboard), capabilities (the objects that can be picked up
  single-handedly), etc. These concepts are probabilistically derived
  from a set of previous activities that are fully and automatically
  observed by computer vision and additional sensor systems. AM-EvA
  models enable robots and technical systems to analyze activities in
  the complete situation and activity context. They render the
  classification and the assessment of actions and situations objective
  and can justify the probabilistic interpretation with respect to the
  activities the concepts have been learned from.
  In this paper, we describe the current state of implementation of the
  system that realizes this idea of automated models of
  everyday activities and show example results from the observation
  and analysis of table setting episodes.},
  keywords = {openease_kbe_humans_table}
}
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