• DocumentCode
    3189120
  • Title

    A novel texture mapping algorithm for planar meshes

  • Author

    Ye, Meng

  • Author_Institution
    Comput. Sch., Wuhan Univ., Wuhan, China
  • fYear
    2011
  • fDate
    8-10 Aug. 2011
  • Firstpage
    4920
  • Lastpage
    4922
  • Abstract
    Presently automatic texture mapping is a hot topic in computer graphics filed. Most previous automatic texture mapping algorithms have suffered from been too slow or could only use a limit set of feature points of the model. We introduce in this paper a new constrained-based method for automatic texture mapping that deal with these problems for planar meshes. Our critical improvements include generalizing feature point to feature curve to fit some application (eg. river, road modeling, etc.) and also simplified computation through efficient weighted of texture mapping. We generalize by parameterizing each vertex at two passes. Firstly we compute all the possible mapping along the feature curve consecutively where every triangle that consists of the computed vertex and two points in the curve can be deduced a conformal mapping result with minimum deformations. Then we combine all the possible mapping using normalization distribution to get the final one. Our results show that this texture mapping algorithm makes a great mapping for the planar meshes.
  • Keywords
    computer graphics; conformal mapping; image texture; mesh generation; normal distribution; automatic texture mapping; computer graphics; conformal mapping; constrained-based method; feature curve; feature point; normalization distribution; planar meshes; Algorithm design and analysis; Computational modeling; Computer graphics; Conformal mapping; Euclidean distance; Rivers; Surface texture; Constrained-based; Planar Meshes‥; Texture Mapping;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
  • Conference_Location
    Deng Leng
  • Print_ISBN
    978-1-4577-0535-9
  • Type

    conf

  • DOI
    10.1109/AIMSEC.2011.6011393
  • Filename
    6011393