• DocumentCode
    1798379
  • Title

    Alignment of face images based on SIFT feature

  • Author

    Zhi-Hui Li ; Ying Hou ; Hai-Bo Liu

  • Author_Institution
    Coll. of Comput. Sci. & Technol., Harbin Eng. Univ., Harbin, China
  • Volume
    2
  • fYear
    2014
  • fDate
    13-16 July 2014
  • Firstpage
    597
  • Lastpage
    600
  • Abstract
    In this paper, a method for the alignment of face images is proposed. We first extract SIFT features from the set of images, match features between each two images. Then we cluster the image according to the number of matching keypoints,in each category. We use the congealing algorithm to train and generate the model. The experiments show that the features are invariant to image scaling and rotation, and partially invariant to the change of illumination. This method has good performance in accuracy and in real-time.
  • Keywords
    face recognition; feature extraction; image matching; transforms; SIFT feature extraction; congealing algorithm; face image-based alignment; illumination change invariance; image clustering; image feature keypoint matching; image rotation invariance; image scaling invariance; Abstracts; Bayes methods; Computational modeling; Face; Congealing; Matching keypoints; SIFT features;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2014 International Conference on
  • Conference_Location
    Lanzhou
  • ISSN
    2160-133X
  • Print_ISBN
    978-1-4799-4216-9
  • Type

    conf

  • DOI
    10.1109/ICMLC.2014.7009675
  • Filename
    7009675