• DocumentCode
    561175
  • Title

    A Robust Affine Invariant Feature Matching Approach

  • Author

    Gao, Ce ; Song, Yixu ; Jia, Peifa

  • Author_Institution
    Tsinghua Nat. Lab. for Inf. Sci. & Technol., Tsinghua Univ., Beijing, China
  • Volume
    1
  • fYear
    2011
  • fDate
    18-21 Dec. 2011
  • Firstpage
    157
  • Lastpage
    160
  • Abstract
    Affine transformation detection can be used in many computer vision and other applications. This paper presents a new method for affine transformation detection. The state-of-the-art methods are mainly divided into two classes. One class is based on complicated descriptors. But this kind of methods need a lot of time to establish and matching the complicated descriptors. The second class is based on probabilistic model. But these methods can not yield good matching result in some difficult conditions. Our method tries to combine the two kinds of methods together, so as to acquire the accuracy and efficiency at the same time.
  • Keywords
    computer vision; image matching; object detection; probability; transforms; affine transformation detection; computer vision; probabilistic model; robust affine invariant feature matching; Accuracy; Computer vision; Detectors; Histograms; Probabilistic logic; Robustness; Training; Affine Invariance; Feature Matching; Learning-Based;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Applications and Workshops (ICMLA), 2011 10th International Conference on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    978-1-4577-2134-2
  • Type

    conf

  • DOI
    10.1109/ICMLA.2011.21
  • Filename
    6146961