Incremental indexing and distributed image search using shared randomized vocabularies

  • Authors:
  • Raphaël Marée;Philippe Denis;Louis Wehenkel;Pierre Geurts

  • Affiliations:
  • University of Liège, Liège, Belgium;University of Liège, Liège, Belgium;University of Liège, Liège, Belgium;University of Liège, Liège, Belgium

  • Venue:
  • Proceedings of the international conference on Multimedia information retrieval
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

We present a cooperative framework for content-based image retrieval for the realistic setting where images are distributed across multiple cooperating servers. The proposed method is in line with bag-of-features approaches but uses fully data-independent, randomized structures, shared by the cooperating servers, to map image features to common visual words. A coherent, global image similarity measure (which is a kernel) is computed in a distributed fashion over visual words, by only requiring a small amount of data transfers between nodes. Our experiments on various image types show that this framework is a very promising step towards large-scale, distributed content-based image retrieval.