ABROA: Audio-Based Room Occupancy with GMMs and HMMs
Rafael Valle, Adrian Freed, Sanjit Seshia, David Wessel

Citation
Rafael Valle, Adrian Freed, Sanjit Seshia, David Wessel. "ABROA: Audio-Based Room Occupancy with GMMs and HMMs". Talk or presentation, 26, October, 2016; Poster presented at the 2015 TerraSwarm Annual Meeting. .

Abstract
This paper outlines preliminary steps towards the development of an audio-based room-occupancy analysis model. Our approach borrows from speech recognition tradition and is based on Gaussian Mixtures and Hidden Markov Models. We analyse possible challenges encountered in the development of such a model, and offer several solutions including feature design and prediction strategies. We provide results obtained from experiments with audio data from a retail store in Palo Alto, California. Model assessment is done via leave-two-out Bootstrap and model convergence achieves good accuracy, thus representing a contribution to multimodal people counting algorithms.

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Citation formats

• HTML

  Rafael Valle, Adrian Freed, Sanjit Seshia, David Wessel.
  <a
  href="http://www.terraswarm.org/pubs/855.html"><i>ABROA:
  Audio-Based Room Occupancy with GMMs and
  HMMs</i></a>, Talk or presentation,  26,
  October, 2016; Poster presented at the <a
  href="http://terraswarm.org/conferences/15/annual"
  >2015 TerraSwarm Annual Meeting</a>.
  .

• Plain text

  Rafael Valle, Adrian Freed, Sanjit Seshia, David Wessel.
  "ABROA: Audio-Based Room Occupancy with GMMs and
  HMMs". Talk or presentation,  26, October, 2016; Poster
  presented at the <a
  href="http://terraswarm.org/conferences/15/annual"
  >2015 TerraSwarm Annual Meeting</a>.
  .

• BibTeX

  @presentation{ValleFreedSeshiaWessel16_ABROAAudioBasedRoomOccupancyWithGMMsHMMs,
      author = {Rafael Valle and Adrian Freed and Sanjit Seshia
                and David Wessel},
      title = {ABROA: Audio-Based Room Occupancy with GMMs and
                HMMs},
      day = {26},
      month = {October},
      year = {2016},
      note = {Poster presented at the <a
                href="http://terraswarm.org/conferences/15/annual"
                >2015 TerraSwarm Annual Meeting</a>.
  },
      abstract = {This paper outlines preliminary steps towards the
                development of an audio-based room-occupancy
                analysis model. Our approach borrows from speech
                recognition tradition and is based on Gaussian
                Mixtures and Hidden Markov Models. We analyse
                possible challenges encountered in the development
                of such a model, and offer several solutions
                including feature design and prediction
                strategies. We provide results obtained from
                experiments with audio data from a retail store in
                Palo Alto, California. Model assessment is done
                via leave-two-out Bootstrap and model convergence
                achieves good accuracy, thus representing a
                contribution to multimodal people counting
                algorithms.},
      URL = {http://terraswarm.org/pubs/855.html}
  }
  

Posted by Rafael Valle on 25 Oct 2016.
Groups: tools