Collections for automatic image annotation and photo tag recommendation

Philip J. Mcparlane, Yashar Moshfeghi, Joemon M. Jose

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

4 Citations (Scopus)

Abstract

This paper highlights a number of problems which exist in the evaluation of existing image annotation and tag recommendation methods. Crucially, the collections used by these state-of-the-art methods contain a number of biases which may be exploited or detrimental to their evaluation, resulting in misleading results. In total we highlight seven issues for three popular annotation evaluation collections, i.e. Corel5k, ESP Game and IAPR, as well as three issues with collections used in two state-of-the-art photo tag recommendation methods. The result of this paper is two freely available Flickr image collections designed for the fair evaluation of image annotation and tag recommendation methods called Flickr-AIA and Flickr-PTR respectively. We show through experimentation and demonstration that these collection are ultimately fairer benchmarks than existing collections.
Original languageEnglish
Title of host publicationMultiMedia Modeling
Subtitle of host publication20th Anniversary International Conference, MMM 2014, Dublin, Ireland, January 6-10, 2014, Proceedings, Part I
Place of PublicationNew York, NY
Pages133-145
Number of pages13
DOIs
Publication statusPublished - 20 Dec 2013
EventInternational Conference on Multimedia Modeling - Dublin, Ireland
Duration: 6 Jan 201410 Jan 2014

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume8325

Conference

ConferenceInternational Conference on Multimedia Modeling
CountryIreland
CityDublin
Period6/01/1410/01/14

Keywords

  • image annotation
  • tag recommendation methods
  • evaluation
  • social media

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  • Cite this

    Mcparlane, P. J., Moshfeghi, Y., & Jose, J. M. (2013). Collections for automatic image annotation and photo tag recommendation. In MultiMedia Modeling: 20th Anniversary International Conference, MMM 2014, Dublin, Ireland, January 6-10, 2014, Proceedings, Part I (pp. 133-145). (Lecture Notes in Computer Science; Vol. 8325). New York, NY. https://doi.org/10.1007/978-3-319-04114-8_12