research-article

Lightweight automatic face annotation in media pages

Authors:

Dmitri Perelman,

Edward Bortnikov,

Roman SandlerAuthors Info & Claims

WWW '12: Proceedings of the 21st international conference on World Wide Web

Pages 939 - 948

https://doi.org/10.1145/2187836.2187962

Published: 16 April 2012 Publication History

Abstract

Labeling human faces in images contained in Web media stories enables enriching the user experience offered by media sites. We propose a lightweight framework for automatic image annotation that exploits named entities mentioned in the article to significantly boost the accuracy of face recognition. While previous works in the area labor to train comprehensive offline visual models for a pre-defined universe of candidates, our approach models the people mentioned in a given story on the y, using a standard Web image search engine as an image sampling mechanism. We overcome multiple sources of noise introduced by this ad-hoc process, to build a fast and robust end-to-end system from off-the-shelf error-prone text analysis and machine vision components. In experiments conducted on approximately 900 faces depicted in 500 stories from a major celebrity news website, we were able to correctly label 81.5% of the faces while mislabeling 14.8% of them.

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Cited By

Bracamonte TBustos BPoblete BSchreck T(2018)Extracting semantic knowledge from web context for multimedia IRMultimedia Tools and Applications10.1007/s11042-017-4997-y77:11(13853-13889)Online publication date: 1-Jun-2018
https://dl.acm.org/doi/10.1007/s11042-017-4997-y
Andrade DMaia LFigueirêdo HViana WTrinta FSouza Baptista C(2018)Photo annotationMultimedia Tools and Applications10.1007/s11042-016-4281-677:1(423-457)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.1007/s11042-016-4281-6

Index Terms

Lightweight automatic face annotation in media pages
1. Applied computing
  1. Computers in other domains
    1. Publishing
2. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks

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Information

Published In

cover image ACM Other conferences

WWW '12: Proceedings of the 21st international conference on World Wide Web

April 2012

1078 pages

ISBN:9781450312295

DOI:10.1145/2187836

General Chairs:
Alain Mille
Université de Lyon, France
,
Fabien Gandon
INRIA, France
,
Jacques Misselis
HP, France
,
Program Chairs:
Michael Rabinovich
Case Western Reserve University, USA
,
Steffen Staab
University of Koblenz-Landau, Germany

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Univ. de Lyon: Universite de Lyon

In-Cooperation

SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 April 2012

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WWW 2012

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Univ. de Lyon

WWW 2012: 21st World Wide Web Conference 2012

April 16 - 20, 2012

Lyon, France

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

Bracamonte TBustos BPoblete BSchreck T(2018)Extracting semantic knowledge from web context for multimedia IRMultimedia Tools and Applications10.1007/s11042-017-4997-y77:11(13853-13889)Online publication date: 1-Jun-2018
https://dl.acm.org/doi/10.1007/s11042-017-4997-y
Andrade DMaia LFigueirêdo HViana WTrinta FSouza Baptista C(2018)Photo annotationMultimedia Tools and Applications10.1007/s11042-016-4281-677:1(423-457)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.1007/s11042-016-4281-6

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