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Combined Retrieval Strategies for Images with and without Distinct Objects

  • Hong Fu
  • Zheru Chi
  • Dagan Feng
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6474)

Abstract

This paper presents the design of an all-season image retrieval system. The system handles the images with and without distinct object(s) using different retrieval strategies. Firstly, based on the visual contrasts and spatial information of an image, a neural network is trained to pre-classify an image as distinct-object or no-distinct-object category by using the Back Propagation Through Structure (BPTS) algorithm. In the second step, an image with distinct object(s) is processed by an attention-driven retrieval strategy emphasizing distinct objects. On the other hand, an image without distinct object(s) (e.g., a scenery images) is processed by a fusing-all retrieval strategy. An improved performance can be obtained by using this combined approach.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Hong Fu
    • 1
    • 2
  • Zheru Chi
    • 1
  • Dagan Feng
    • 1
    • 3
  1. 1.Department of Electronic and Information EngineeringThe Hong Kong Polytechnic UniversityHong Kong
  2. 2.Department of Computer ScienceChu Hai College of Higher EducationHong Kong
  3. 3.School of Information TechnologiesThe University of SydneyAustralia

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