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Historical image annotation by exploring the tag relevance

  • Junjie Zhang
  • , Jian Zhang
  • , Qi Wu
  • , Qiang Wu
  • , Jinsong Xu
  • , Jianfeng Lu
  • , Robin Phua
  • , Kate Curr
  • , Zhenmin Tang
  • University of Technology Sydney
  • Nanjing University of Science and Technology
  • University of Adelaide
  • State Library of New South Wales

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

1 Citation (Scopus)

Abstract

Historical images usually contain enormous historical research value and are highly related to the history objects, events and background stories etc. Therefore, annotating these images always requires selecting tags within a large set. In this paper, we propose to annotate historical images by exploring the tag relevance. We measure the tag relevance from three different perspectives, including its visual relevance, its dependencies with other tags and its relationship with location based meta-data. By using tag relevance as guidance, we generate three tag sub-sets and use them to fulfill the annotation. Experimental results on the benchmark dataset indicate the significance of exploring the tag relevance by comparing with the baseline experiments.

Original languageEnglish
Title of host publicationProceedings - 4th Asian Conference on Pattern Recognition, ACPR 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages646-651
Number of pages6
ISBN (Electronic)9781538633540
DOIs
Publication statusPublished - 13 Dec 2018
Externally publishedYes
Event4th Asian Conference on Pattern Recognition, ACPR 2017 - Nanjing, China
Duration: 26 Nov 2017 → 29 Nov 2017

Publication series

NameProceedings - 4th Asian Conference on Pattern Recognition, ACPR 2017

Conference

Conference4th Asian Conference on Pattern Recognition, ACPR 2017
Country/TerritoryChina
CityNanjing
Period26/11/17 → 29/11/17

Keywords

  • Annotation
  • Historical images
  • Tag relevance

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