Citation
Matt Weber, Edward A. Lee. "Poster Abstract: A Model For Semantic Localization". Talk or presentation, April, 2015.

Abstract
We propose a model for Semantic Localization, i.e. establishing positional relations on meaningful objects, to enable the principled integration of heterogenous localization clues { such as those derived from ubiquitous sensors in the Internet of Things. Our approach is two-pronged: we consider relation-structured Phenomenal Maps alongside spatially-organized Physical Maps. Phenomenal Maps may be used to answer semantic queries about the relative position of objects without necessarily resorting to physical coordinates. Physical Maps are not restricted to purely Euclidian spaces, to the contrary we identify useful applications for topological, and metrical maps among others. We give the framework for a structured mechanism through which localization information in all these representations may be reconciled.

Electronic downloads

• WeberLee_SemanticLocalization_PosterAbstract_IPSN.pdf · application/x-octet-stream · 2215 kbytes

• HTML

  Matt Weber, Edward A. Lee. <a
  href="http://chess.eecs.berkeley.edu/pubs/1094.html"
  ><i>Poster Abstract: A Model For Semantic
  Localization</i></a>, Talk or presentation, 
  April, 2015.

• Plain text

  Matt Weber, Edward A. Lee. "Poster Abstract: A Model
  For Semantic Localization". Talk or presentation, 
  April, 2015.

• BibTeX

  @presentation{WeberLee15_PosterAbstractModelForSemanticLocalization,
      author = {Matt Weber and Edward A. Lee},
      title = {Poster Abstract: A Model For Semantic Localization},
      month = {April},
      year = {2015},
      abstract = {We propose a model for Semantic Localization, i.e.
                establishing positional relations on meaningful
                objects, to enable the principled integration of
                heterogenous localization clues { such as those
                derived from ubiquitous sensors in the Internet of
                Things. Our approach is two-pronged: we consider
                relation-structured Phenomenal Maps alongside
                spatially-organized Physical Maps. Phenomenal Maps
                may be used to answer semantic queries about the
                relative position of objects without necessarily
                resorting to physical coordinates. Physical Maps
                are not restricted to purely Euclidian spaces, to
                the contrary we identify useful applications for
                topological, and metrical maps among others. We
                give the framework for a structured mechanism
                through which localization information in all
                these representations may be reconciled.},
      URL = {http://chess.eecs.berkeley.edu/pubs/1094.html}
  }
  

Posted by Mary Stewart on 9 Mar 2015.
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