• DocumentCode
    3262879
  • Title

    Realization of affine SIFT real-time image processing for home service robot

  • Author

    Ying-Hao Wang ; Hao-En Cheng ; Chih-Jui Lin ; Ri-Wei Deng ; Hsuan Lee ; Li, Tzuu-Hseng S.

  • Author_Institution
    Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
  • fYear
    2013
  • fDate
    4-6 July 2013
  • Firstpage
    141
  • Lastpage
    146
  • Abstract
    This paper mainly discusses the realization of affine Scale-Invariant Feature Transform (SIFT) real-time image processing method for “May” who is a home service robot designed and implemented by aiRobots laboratory. Firstly, a six-step method is proposed to create image database. Then the SIFT algorithm is adopted to detect features with this database, the error rate of features is reduced. Integration of the six-step method and SIFT can significantly decrease time for setting up the database. Thirdly, the object-recognition vision system is built up by parallel Affine-SIFT (ASIFT) algorithm, where the OpenGL is used to reduce the calculation time of affine projection and SiftGPU (Graphics Processing Unit) is adopted to accomplish the real-time operation speed of SIFT. Finally, the real-time grasping experiments demonstrate the feasibility and validity of the proposed scheme.
  • Keywords
    graphics processing units; manipulators; object detection; robot vision; service robots; transforms; ASIFT; OpenGL; SiftGPU; affine SIFT real-time image processing; affine projection; aiRobots laboratory; feature detection; graphics processing unit; home service robot; real-time grasping experiments; scale-invariant feature transform; Cameras; Central Processing Unit; Databases; Feature extraction; Graphics processing units; Instruction sets; Real-time systems; Affine-SIFT; OpenGL; SIFT; home service robot May; real-time image processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    System Science and Engineering (ICSSE), 2013 International Conference on
  • Conference_Location
    Budapest
  • ISSN
    2325-0909
  • Print_ISBN
    978-1-4799-0007-7
  • Type

    conf

  • DOI
    10.1109/ICSSE.2013.6614648
  • Filename
    6614648