Invention Grant
US09202109B2 Method, apparatus and computer readable recording medium for detecting a location of a face feature point using an Adaboost learning algorithm 有权
用于使用Adaboost学习算法检测脸部特征点的位置的方法,装置和计算机可读记录介质

  • Patent Title: Method, apparatus and computer readable recording medium for detecting a location of a face feature point using an Adaboost learning algorithm
  • Patent Title (中): 用于使用Adaboost学习算法检测脸部特征点的位置的方法,装置和计算机可读记录介质
  • Application No.: US14129356
    Application Date: 2012-09-27
  • Publication No.: US09202109B2
    Publication Date: 2015-12-01
  • Inventor: Yeongjae CheonYongchan Park
  • Applicant: Yeongjae CheonYongchan Park
  • Applicant Address: US CA Santa Clara
  • Assignee: Intel Corporation
  • Current Assignee: Intel Corporation
  • Current Assignee Address: US CA Santa Clara
  • Agency: Blakely, Sokoloff, Taylor & Zafman LLP
  • Priority: KR10-2011-0097794 20110927
  • International Application: PCT/KR2012/007843 WO 20120927
  • International Announcement: WO2013/048159 WO 20130404
  • Main IPC: G06K9/00
  • IPC: G06K9/00 G06K9/32 G06K9/62
Method, apparatus and computer readable recording medium for detecting a location of a face feature point using an Adaboost learning algorithm
Abstract:
The present disclosure relates to detecting the location of a face feature point using an Adaboost learning algorithm. According to some embodiments, a method for detecting a location of a face feature point comprises: (a) a step of classifying a sub-window image into a first recommended feature point candidate image and a first non-recommended feature point candidate image using first feature patterns selected by an Adaboost learning algorithm, and generating first feature point candidate location information on the first recommended feature point candidate image; and (b) a step of re-classifying said sub-window image classified into said first non-recommended feature point candidate image, into a second recommended feature point candidate image and a second non-recommended feature point candidate image using second feature patterns selected by the Adaboost learning algorithm, and generating second feature point candidate location information on the second recommended feature point recommended candidate image.
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