ImageSense

  • Authors:
  • Lusong Li;Tao Mei;Xian-Sheng Hua;Shipeng Li

  • Affiliations:
  • Beihang University, Beijing, China;Microsoft Research Asia, Beijing, China;Microsoft Research Asia, Beijing, China;Microsoft Research Asia, Beijing, China

  • Venue:
  • MM '08 Proceedings of the 16th ACM international conference on Multimedia
  • Year:
  • 2008

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Abstract

This demonstration presents an innovative contextual advertising platform for online image service, called ImageSense. Unlike most current ad-networks which treat image advertising as general text advertising by displaying relevant ads based on the contents of the Web page, ImageSense aims to embed more contextually relevant ads at less intrusive positions within each suitable image. Given a Web page containing images, ImageSense is able to decompose the page into a set of semantic blocks, select the suitable images from these blocks for advertising, rank the ads according to the relevance derived from surrounding text and visual similarity, and insert the relevant ads into the nonintrusive areas within the selected images. ImageSense represents one of the first attempts towards contextual image advertising which enables both the publishers and advertisers deliver more effective ads carried through image contents.