ImageWebs: Computing and exploiting connectivity in image collections

  • Kyle Heath
  • , Natasha Gelfand
  • , Maks Ovsjanikov
  • , Mridul Aanjaneya
  • , Leonidas J. Guibas

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

Abstract

The widespread availability of digital cameras and ubiquitous Internet access have facilitated the creation of massive image collections. These collections can be highly interconnected through implicit links between image pairs viewing the same or similar objects. We propose building graphs called Image Webs to represent such connections. While earlier efforts studied local neighborhoods of such graphs, we are interested in understanding global structure and exploiting connectivity at larger scales. We show how to efficiently construct Image Webs that capture the connectivity in an image collection using spectral graph theory. Our technique can link together tens of thousands of images in a few minutes using a computer cluster. We also demonstrate applications for exploring collections based on global topological analysis.

Original languageEnglish
Title of host publication2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010
Pages3432-3439
Number of pages8
DOIs
Publication statusPublished - 31 Aug 2010
Externally publishedYes
Event2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010 - San Francisco, CA, United States
Duration: 13 Jun 201018 Jun 2010

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN (Print)1063-6919

Conference

Conference2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010
Country/TerritoryUnited States
CitySan Francisco, CA
Period13/06/1018/06/10

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