Visual summarization of the social image collection using image attractiveness learned from social behaviors

Jin Woo Jeong, Hyun Ki Hong, Jee Uk Heu, Iqbal Qasim, Dong Ho Lee

Research output: Contribution to journalConference articlepeer-review

5 Scopus citations

Abstract

How to effectively summarize a large-scale image collection is still an important and open problem. In this paper, we propose a novel method to effectively generate a summary of the social image collection using image attractiveness learned from the social behaviors conducted in Flickr. To this end, we exploit the note information of Flickr images. The notes of Flickr images are user generated bounding boxes with text annotations assigned on the interesting image regions. Using the visual features extracted from the images that have notes, we have generated the attractiveness models for various concepts. Finally, the attractiveness models are exploited to make a summary of the social image collection. Through various user studies on the image collections from Flickr groups, we show the feasibility of our method and discuss further directions.

Original languageEnglish
Article number6298457
Pages (from-to)538-543
Number of pages6
JournalProceedings - IEEE International Conference on Multimedia and Expo
DOIs
StatePublished - 2012
Event2012 13th IEEE International Conference on Multimedia and Expo, ICME 2012 - Melbourne, VIC, Australia
Duration: 9 Jul 201213 Jul 2012

Keywords

  • Flickr note
  • image attractiveness
  • image interestingness
  • image summary
  • search result clustering

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