• DocumentCode
    3318039
  • Title

    Graphic retrieval based on limited semantics

  • Author

    Li, Hanjing ; Zhao, Tiejun ; Li, Sheng

  • Author_Institution
    Compt. Sci. & Technol. Sch., Harbin Inst. of Technol., China
  • fYear
    2005
  • fDate
    30 Oct.-1 Nov. 2005
  • Firstpage
    535
  • Lastpage
    539
  • Abstract
    Online graphic resources have grown rapidly. Methods for graphic retrieval have likewise improved including semantics-based graphic retrieval and content-based graphic retrieval. For content-based graphic retrieval users must input a draft drawing or sample image. For some tasks, such as converting text to scene, it is impossible to provide a draft. Presently semantics-based graphic retrieval is dependent on previously tagged details about the graphic. We propose a method based only on the semantic and morph similarity of the graphic file name which does not need additional graphic specifications. Experimental results have demonstrated the effectiveness of our method.
  • Keywords
    computer graphics; content-based retrieval; content-based graphic retrieval; draft drawing; graphic specification; morph similarity; sample image; semantics-based graphic retrieval; Animation; Databases; Frequency; Graphics; Information retrieval; Mice; Natural languages; Shape; Taxonomy; Graphic Retrieval; Semantic Database; Similarity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Language Processing and Knowledge Engineering, 2005. IEEE NLP-KE '05. Proceedings of 2005 IEEE International Conference on
  • Print_ISBN
    0-7803-9361-9
  • Type

    conf

  • DOI
    10.1109/NLPKE.2005.1598795
  • Filename
    1598795