• DocumentCode
    594974
  • Title

    Symmetric object detection based on symmetry and centripetal-SIFT edge descriptor

  • Author

    Yin Xiang ; Shutao Li

  • Author_Institution
    Coll. of Electr. & Inf. Eng., Hunan Univ. Changsha, Changsha, China
  • fYear
    2012
  • fDate
    11-15 Nov. 2012
  • Firstpage
    1403
  • Lastpage
    1406
  • Abstract
    This paper proposes a new edge descriptor named centripetal-SIFT edge descriptor. A method for symmetric object detection is presented based on symmetry and centripetal-SIFT descriptor in real unsegmented images. Our method includes three main steps: 1) The dominant symmetry axis is located based on SIFT feature point; 2) Image edge points are extracted in scale space and described by the proposed centripetal-SIFT descriptor; 3) Symmetric objects are located as the result of computing symmetric edge points. The superior performance of our method is demonstrated by experimental results under complex backgrounds.
  • Keywords
    edge detection; feature extraction; object detection; SIFT feature point; centripetal-SIFT edge descriptor; dominant symmetry axis; edge point extraction; scale invariant feature transform; symmetric object detection; symmetry; Distributed databases; Feature extraction; Force; Image edge detection; Noise measurement; Object detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2012 21st International Conference on
  • Conference_Location
    Tsukuba
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4673-2216-4
  • Type

    conf

  • Filename
    6460403