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NicePic!: a system for extracting attractive photos from flickr streams

Published: 03 July 2014 Publication History

Abstract

A large number of images are continuously uploaded to popular photo sharing websites and online social communities. In this demonstration we show a novel application which automatically classifies images in a live photo stream according to their attractiveness for the community, based on a number of visual and textual features. The system effectively introduces an additional facet to browse and explore photo collections by highlighting the most attractive photographs and demoting the least attractive.

References

[1]
J. S. Hare, S. Samangooei, and D. Dupplaw. Openimaj and imageterrier: Java libraries and tools for scalable multimedia analysis and indexing of images. In ACM MM'11.
[2]
T. Joachims. Making large-scale support vector machine learning practical. Advances in kernel methods: support vector learning, pages 169--184, 1999.
[3]
J. San Pedro and S. Siersdorfer. Ranking and classifying attractiveness of photos in folksonomies. In WWW '09.
[4]
J. San Pedro, T. Yeh, and N. Oliver. Leveraging user comments for aesthetic aware image search reranking. In WWW '12.

Cited By

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  • (2017)Identifying and ranking cultural heritage resources on geotagged social media for smart cultural tourism servicesPersonal and Ubiquitous Computing10.1007/s00779-016-0992-y21:2(267-279)Online publication date: 1-Apr-2017
  • (2016)A survey on Flickr multimedia research challengesEngineering Applications of Artificial Intelligence10.1016/j.engappai.2016.01.00651:C(71-91)Online publication date: 1-May-2016

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  1. NicePic!: a system for extracting attractive photos from flickr streams

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      cover image ACM Conferences
      SIGIR '14: Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval
      July 2014
      1330 pages
      ISBN:9781450322577
      DOI:10.1145/2600428
      Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 03 July 2014

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      Author Tags

      1. flickr
      2. image attractivness
      3. sift
      4. svm classifier
      5. visual features
      6. webservice

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      • Demonstration

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      SIGIR '14
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      SIGIR '14 Paper Acceptance Rate 82 of 387 submissions, 21%;
      Overall Acceptance Rate 792 of 3,983 submissions, 20%

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      Cited By

      View all
      • (2017)Identifying and ranking cultural heritage resources on geotagged social media for smart cultural tourism servicesPersonal and Ubiquitous Computing10.1007/s00779-016-0992-y21:2(267-279)Online publication date: 1-Apr-2017
      • (2016)A survey on Flickr multimedia research challengesEngineering Applications of Artificial Intelligence10.1016/j.engappai.2016.01.00651:C(71-91)Online publication date: 1-May-2016

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