skip to main content
10.1145/1571941.1572101acmconferencesArticle/Chapter ViewAbstractPublication PagesirConference Proceedingsconference-collections
poster

Multiclass VisualRank: image ranking method in clustered subsets based on visual features

Authors Info & Claims
Published:19 July 2009Publication History

ABSTRACT

This paper proposes Multiclass VisualRank, a method that expands the idea of VisualRank into more than one category of images. Multiclass VisualRank divides images retrieved from search engines into several categories based on distinctive patterns of visual features, and gives ranking within the category. Experimental results show that our method can extract several different image categories relevant to given keyword and gives good ranking scores to retrieved images.

References

  1. S.Brin and L.Page. The anatomy of a large-scalehypertextual Web search engine. Computer Networks and ISDN Systems, 30(1--7):107--117, Apr. 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Y.Jing and S.Baluja. VisualRank: Applying PageRank to large-scale image search. PAMI, 30(11):1877--1890, Nov. 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. D.G.Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 60(2):91--110, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. J.Shi and J.Malik. Normalized cuts and image segmentation. PAMI, 22(8):888--905, Aug. 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Multiclass VisualRank: image ranking method in clustered subsets based on visual features

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Conferences
          SIGIR '09: Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
          July 2009
          896 pages
          ISBN:9781605584836
          DOI:10.1145/1571941

          Copyright © 2009 Copyright is held by the author/owner(s)

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 19 July 2009

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • poster

          Acceptance Rates

          Overall Acceptance Rate792of3,983submissions,20%

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader