Visual image search: feature signatures or/and global descriptors

  • Authors:
  • Jakub Lokoč;David Novák;Michal Batko;Tomáš Skopal

  • Affiliations:
  • SIRET Research Group, Faculty of Mathematics and Physics, Charles University in Prague, Czech Republic;Faculty of Informatics, Masaryk University in Brno, Czech Republic;Faculty of Informatics, Masaryk University in Brno, Czech Republic;SIRET Research Group, Faculty of Mathematics and Physics, Charles University in Prague, Czech Republic

  • Venue:
  • SISAP'12 Proceedings of the 5th international conference on Similarity Search and Applications
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

The success of content-based retrieval systems stands or falls with the quality of the utilized similarity model. In the case of having no additional keywords or annotations provided with the multimedia data, the hard task is to guarantee the highest possible retrieval precision using only content-based retrieval techniques. In this paper we push the visual image search a step further by testing effective combination of two orthogonal approaches --- the MPEG-7 global visual descriptors and the feature signatures equipped by the Signature Quadratic Form Distance. We investigate various ways of descriptor combinations and evaluate the overall effectiveness of the search on three different image collections. Moreover, we introduce a new image collection, TWIC, designed as a larger realistic image collection providing ground truth. In all the experiments, the combination of descriptors proved its superior performance on all tested collections. Furthermore, we propose a re-ranking variant guaranteeing efficient yet effective image retrieval.