Combined retrieval strategies for images with and without distinct objects

Hong Fu, Zheru Chi, Dagan Feng

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review


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.
Original languageEnglish
Title of host publicationAdvanced Concepts for Intelligent Vision Systems - 12th International Conference, ACIVS 2010, Proceedings
Number of pages8
EditionPART 1
Publication statusPublished - 1 Dec 2010
Event12th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2010 - Sydney, NSW, Australia
Duration: 13 Dec 201016 Dec 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume6474 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference12th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2010
CitySydney, NSW

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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