SigAlbum: An embedded photo service using a tiny text intelligence

Hae Yong Shin, Woo Jong Ryu, Hyeon Taek Oh, Sang-Geun Lee

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

5 Citations (Scopus)

Abstract

We demonstrate sigAlbum, a novel photo album service. It utilizes a tiny text intelligence to intelligently classify and search relevant photos inside a smartphone without any image processing. sigAlbum has three key features. First, it organizes in-device photos into well-defined categories. Secondly, it retrieves semantically related photos. Finally, it works in a stand-Alone, privacy-protecting manner. To the best of our knowledge, this is the first work that provides intelligent classification and semantic search services without resort to the cloud server.

Original languageEnglish
Title of host publicationUbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing
PublisherAssociation for Computing Machinery, Inc
Pages373-376
Number of pages4
ISBN (Electronic)9781450344623
DOIs
Publication statusPublished - 2016 Sep 12
Event2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016 - Heidelberg, Germany
Duration: 2016 Sep 122016 Sep 16

Other

Other2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016
CountryGermany
CityHeidelberg
Period16/9/1216/9/16

Keywords

  • Intelligent photo service
  • Semantic search
  • Text classification
  • Tiny text intelligence

ASJC Scopus subject areas

  • Hardware and Architecture
  • Software
  • Information Systems
  • Computer Networks and Communications
  • Human-Computer Interaction

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  • Cite this

    Shin, H. Y., Ryu, W. J., Oh, H. T., & Lee, S-G. (2016). SigAlbum: An embedded photo service using a tiny text intelligence. In UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 373-376). Association for Computing Machinery, Inc. https://doi.org/10.1145/2968219.2971371