Poster abstract: Intuitive appliance identification using image matching in smart buildings

Kaifei Chen, John Kolb, Jonathan Fürsty, Dezhi Hongz, Randy H. Katz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Identifying an appliance for interaction in commercial buildings becomes non-trivial as the number of smart appliances explodes. We present a system for users to intuitively "look up" appliances using image matching-based technique on a pre-constructed and annotated visual model of building interiors. It matched 98% images on a public robot-collected dataset and achieved 100% recall and precision. Our lab experiments with human captured videos and images also show the feasibility of real world deployments.

Original languageEnglish (US)
Title of host publicationBuildSys 2015 - Proceedings of the 2nd ACM International Conference on Embedded Systems for Energy-Efficient Built
PublisherAssociation for Computing Machinery, Inc
Pages103-104
Number of pages2
ISBN (Electronic)9781450339810
DOIs
StatePublished - Nov 4 2015
Externally publishedYes
Event2nd ACM International Conference on Embedded Systems for Energy-Efficient Built, BuildSys 2015 - Seoul, Korea, Republic of
Duration: Nov 4 2015Nov 5 2015

Publication series

NameBuildSys 2015 - Proceedings of the 2nd ACM International Conference on Embedded Systems for Energy-Efficient Built

Conference

Conference2nd ACM International Conference on Embedded Systems for Energy-Efficient Built, BuildSys 2015
Country/TerritoryKorea, Republic of
CitySeoul
Period11/4/1511/5/15

Bibliographical note

Publisher Copyright:
© 2015 ACM.

Keywords

  • Identification
  • Image Matching
  • Structure from Motion

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