Probabilistic image tagging with tags expanded by text-based search

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Automatic image tagging automatically assigns image with semantic keywords called tags, which significantly facilitates image search and organization. Most of present image tagging approaches assign the query image with the tags derived from the visually similar images in the training dataset only. However, their scalabilities and performances are constrained by the limitation of using the training method and the fixed size tag vocabulary. In this paper, we proposed a search based probabilistic image tagging algorithm (CTSTag), in which the initially assigned tags are mined from the content-based search result and expanded from the text-based search results. Experiments on NUS-WIDE dataset show not only the performance of the proposed algorithm but also the advantage of image retrieval using the tagging result.

Original languageEnglish
Title of host publicationDatabase Systems for Advanced Applications - 16th International Conference, DASFAA 2011, Proceedings
Pages269-283
Number of pages15
EditionPART 1
DOIs
StatePublished - 2011
Event16th International Conference on Database Systems for Advanced Applications, DASFAA 2011 - Hong Kong, China
Duration: 22 Apr 201125 Apr 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume6587 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Database Systems for Advanced Applications, DASFAA 2011
Country/TerritoryChina
CityHong Kong
Period22/04/1125/04/11

Keywords

  • Image tagging
  • search based tagging
  • tag expansion

Fingerprint

Dive into the research topics of 'Probabilistic image tagging with tags expanded by text-based search'. Together they form a unique fingerprint.

Cite this