• DocumentCode
    2572337
  • Title

    Pose recognition of giant pandas based on gradient shapes

  • Author

    Juan Chen ; Quan Wen ; Chenglong Zhuo ; Mete, Mutlu

  • Author_Institution
    Sch. of Comput. Sci. & Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
  • fYear
    2012
  • fDate
    19-21 Oct. 2012
  • Firstpage
    358
  • Lastpage
    362
  • Abstract
    In this paper, we proposed a novel approach towards the pose recognition of giant pandas based on the gradient shapes. The proposed approach is implemented in three main steps. First, the gradient contour is extracted by filtering the internal pixels in the gradient image. Second, a novel region partition method is used to measure the body weight of giant panda in different image directions. Third, the Fuzzy C-Means clustering is utilized to recognize various poses of giant panda based on the gradient shapes. Extensive experiments are carried out to validate the performance of the proposed method. The experimental results demonstrate that our method is quite promising.
  • Keywords
    feature extraction; filtering theory; fuzzy set theory; gradient methods; pattern clustering; performance evaluation; pose estimation; shape recognition; zoology; body weight measurement; fuzzy C-means clustering; giant panda; gradient contour extraction; gradient image; gradient shapes; image directions; internal pixel filtering; performance validation; pose recognition; region partition method; Face; Feature extraction; Filtering; Image edge detection; Shape; Vectors; Fuzzy C-Means; giant panda; gradient; pose recognition; shape features;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Problem-Solving (ICCP), 2012 International Conference on
  • Conference_Location
    Leshan
  • Print_ISBN
    978-1-4673-1696-5
  • Electronic_ISBN
    978-1-4673-1695-8
  • Type

    conf

  • DOI
    10.1109/ICCPS.2012.6384309
  • Filename
    6384309