Fuzzy based contextual cueing for region level annotation

Sheng Hua Zhong, Yan Liu, Yang Liu, Fu Lai Korris Chung

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

Abstract

This paper investigates the challenging issue of assigning given image-level annotations to precise regions on natural images. We propose a novel label to region assignment (LRA) technique called Fuzzy-based Contextual-cueing Label Propagation (FCLP) with four parts: First, an image is over-segmented into a set of atomic patches and the local visual information of color features and texture features are extracted. Second, fuzzy representation and fuzzy reasoning are used to model contextual cueing information, especially for the imprecise position information and ambiguous spatial topological relationships. Third, labels are propagated inter images in visual space and intra images in contextual cueing space. Finally, the fuzzy C-means clustering based on K-nearest neighbor (KNN-FCM) is utilized to segment the images into semantic regions and associate with corresponding annotations. Experiments on the public datasets demonstrate the effectiveness of the proposed technique.
Original languageEnglish
Title of host publicationProceedings of the 2nd International Conference on Internet Multimedia Computing and Service, ICIMCS'10
Pages1-6
Number of pages6
DOIs
Publication statusPublished - 1 Dec 2010
Event2nd International Conference on Internet Multimedia Computing and Service, ICIMCS 2010 - Harbin, China
Duration: 30 Dec 201031 Dec 2010

Conference

Conference2nd International Conference on Internet Multimedia Computing and Service, ICIMCS 2010
CountryChina
CityHarbin
Period30/12/1031/12/10

Keywords

  • Contextual cueing
  • Fuzzy theory
  • Label to region assignment

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Human-Computer Interaction
  • Software

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