Finding visual concepts by web image mining

Keiji Yanai, Jacobus J Barnard

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

7 Citations (Scopus)

Abstract

We propose measuring "visualness" of concepts with images on the Web, that is, what extent concepts have visual characteristics. This is a new application of "Web image mining". To know which concept has visually discriminative power is important for image recognition, since not all concepts are related to visual contents. Mining image data on the Web with our method enables it. Our method performs probabilistic region selection for images and computes an entropy measure which represents "visualness" of concepts. In the experiments, we collected about forty thousand images from the Web for 150 concepts. We examined which concepts are suitable for annotation of image contents.

Original languageEnglish (US)
Title of host publicationProceedings of the 15th International Conference on World Wide Web
Pages923-924
Number of pages2
DOIs
StatePublished - 2006
Event15th International Conference on World Wide Web - Edinburgh, Scotland, United Kingdom
Duration: May 23 2006May 26 2006

Other

Other15th International Conference on World Wide Web
CountryUnited Kingdom
CityEdinburgh, Scotland
Period5/23/065/26/06

Fingerprint

Image recognition
Entropy
Experiments

Keywords

  • Image recognition
  • Probabilistic method
  • Web image mining

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software

Cite this

Yanai, K., & Barnard, J. J. (2006). Finding visual concepts by web image mining. In Proceedings of the 15th International Conference on World Wide Web (pp. 923-924) https://doi.org/10.1145/1135777.1135946

Finding visual concepts by web image mining. / Yanai, Keiji; Barnard, Jacobus J.

Proceedings of the 15th International Conference on World Wide Web. 2006. p. 923-924.

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

Yanai, K & Barnard, JJ 2006, Finding visual concepts by web image mining. in Proceedings of the 15th International Conference on World Wide Web. pp. 923-924, 15th International Conference on World Wide Web, Edinburgh, Scotland, United Kingdom, 5/23/06. https://doi.org/10.1145/1135777.1135946
Yanai K, Barnard JJ. Finding visual concepts by web image mining. In Proceedings of the 15th International Conference on World Wide Web. 2006. p. 923-924 https://doi.org/10.1145/1135777.1135946
Yanai, Keiji ; Barnard, Jacobus J. / Finding visual concepts by web image mining. Proceedings of the 15th International Conference on World Wide Web. 2006. pp. 923-924
@inproceedings{08264d1b114c452c8c09fc447424057d,
title = "Finding visual concepts by web image mining",
abstract = "We propose measuring {"}visualness{"} of concepts with images on the Web, that is, what extent concepts have visual characteristics. This is a new application of {"}Web image mining{"}. To know which concept has visually discriminative power is important for image recognition, since not all concepts are related to visual contents. Mining image data on the Web with our method enables it. Our method performs probabilistic region selection for images and computes an entropy measure which represents {"}visualness{"} of concepts. In the experiments, we collected about forty thousand images from the Web for 150 concepts. We examined which concepts are suitable for annotation of image contents.",
keywords = "Image recognition, Probabilistic method, Web image mining",
author = "Keiji Yanai and Barnard, {Jacobus J}",
year = "2006",
doi = "10.1145/1135777.1135946",
language = "English (US)",
isbn = "1595933239",
pages = "923--924",
booktitle = "Proceedings of the 15th International Conference on World Wide Web",

}

TY - GEN

T1 - Finding visual concepts by web image mining

AU - Yanai, Keiji

AU - Barnard, Jacobus J

PY - 2006

Y1 - 2006

N2 - We propose measuring "visualness" of concepts with images on the Web, that is, what extent concepts have visual characteristics. This is a new application of "Web image mining". To know which concept has visually discriminative power is important for image recognition, since not all concepts are related to visual contents. Mining image data on the Web with our method enables it. Our method performs probabilistic region selection for images and computes an entropy measure which represents "visualness" of concepts. In the experiments, we collected about forty thousand images from the Web for 150 concepts. We examined which concepts are suitable for annotation of image contents.

AB - We propose measuring "visualness" of concepts with images on the Web, that is, what extent concepts have visual characteristics. This is a new application of "Web image mining". To know which concept has visually discriminative power is important for image recognition, since not all concepts are related to visual contents. Mining image data on the Web with our method enables it. Our method performs probabilistic region selection for images and computes an entropy measure which represents "visualness" of concepts. In the experiments, we collected about forty thousand images from the Web for 150 concepts. We examined which concepts are suitable for annotation of image contents.

KW - Image recognition

KW - Probabilistic method

KW - Web image mining

UR - http://www.scopus.com/inward/record.url?scp=34250630123&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34250630123&partnerID=8YFLogxK

U2 - 10.1145/1135777.1135946

DO - 10.1145/1135777.1135946

M3 - Conference contribution

AN - SCOPUS:34250630123

SN - 1595933239

SN - 9781595933232

SP - 923

EP - 924

BT - Proceedings of the 15th International Conference on World Wide Web

ER -