Visual summarization for place-of-interest by social-contextual constrained geo-clustering

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

With the rapid development of social networks, more and more users choose to share their own photos with their friends. Especially, users prefer to share the photos they took during traveling, thus there emerges many user generated content for place-of-interests (POIs). So based on the user contributed photos, we can summarize each POI by mining location-of-interest (LOI, which represents the attractive viewpoints of POI) and selecting some representative images from them. It is important for scheduling a traveling, and in this paper, an effective POI summarization approach is proposed by an improved geo-clustering with visual and views verification, which helps us to have a representative and comprehensive perception for POI. In our approach, we firstly collect POI related photos from social media, and filter the raw data by the combination of tags and geo-locations. Secondly, we mine LOIs for each POI by the improved geo-location clustering method. Finally, we employ visual and views verification to select images from LOIs to summarize the POI. We conduct a series of experiments based on Flcoickr dataset. Experimental results demonstrate the effectiveness of our proposed method.

Original languageEnglish
Title of host publication2015 IEEE 17th International Workshop on Multimedia Signal Processing, MMSP 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467374781
DOIs
StatePublished - 30 Nov 2015
Event17th IEEE International Workshop on Multimedia Signal Processing, MMSP 2015 - Xiamen, China
Duration: 19 Oct 201521 Oct 2015

Publication series

Name2015 IEEE 17th International Workshop on Multimedia Signal Processing, MMSP 2015

Conference

Conference17th IEEE International Workshop on Multimedia Signal Processing, MMSP 2015
Country/TerritoryChina
CityXiamen
Period19/10/1521/10/15

Keywords

  • Clustering algorithms
  • Encyclopedias
  • Filtering
  • Internet
  • Media
  • Visualization

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