• DocumentCode
    249184
  • Title

    Context-aware codebook learning for mobile landmark recognition

  • Author

    Tao Chen ; Jiayuan Fan ; Shijian Lu

  • Author_Institution
    Inst. for Infocomm Res., Agency for Sci., Technol. & Res., Singapore, Singapore
  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    3963
  • Lastpage
    3967
  • Abstract
    This paper presents a codebook learning based mobile landmark recognition technique based on context information that is acquired from mobile devices. Previous codebook learning methods are mainly developed on nonmobile platforms such as desktop PC, hence underutilize context features such as location and direction information as provided by the mobile devices. The proposed technique employs both the direction and location information to learn the codebook for mobile landmark recognition. A set of direction-aware leaf codewords are first generated by using direction data to decompose the leaf nodes of the original SVT. A visual word significance learning algorithm is then developed by considering location information to generate a compact codebook for image encoding. Experiments on the NTU50Landmark database show that the proposed method can achieve good recognition performance in mobile landmark recognition.
  • Keywords
    image coding; image recognition; learning (artificial intelligence); mobile computing; NTU50Landmark database; SVT; context information; context-aware codebook learning; desktop PC; direction information; direction-aware leaf codewords; image encoding; location information; mobile devices; mobile landmark recognition technique; nonmobile platforms; underutilize context features; visual word significance learning algorithm; Context; Feature extraction; Global Positioning System; Histograms; Image recognition; Mobile communication; Visualization; GPS; SVT; codebook learning; direction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2014 IEEE International Conference on
  • Conference_Location
    Paris
  • Type

    conf

  • DOI
    10.1109/ICIP.2014.7025805
  • Filename
    7025805