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文章基本信息

  • 标题:Computationally Efficient Invariant Facial Expression Recognition
  • 本地全文:下载
  • 作者:Hussain Muhammad ; SajidAli Khan ; Ullah Nadeem
  • 期刊名称:Research Journal of Recent Sciences
  • 电子版ISSN:2277-2502
  • 出版年度:2014
  • 卷号:3
  • 期号:2
  • 页码:61-68
  • 语种:English
  • 出版社:International Science Community Association
  • 摘要:The most important bottleneck for facial expression recognition system is recognizing the expression in uncontrolled environments with minimum computational time consumption. This problem has been addressed by combining the robust local texture descriptors which are invariant to illumination effects. In this work, the illumination effects are eliminated by using Weber Local Descriptor (WLD). Next, Local Ternary Descriptor (LTP) was introduced to preserved discriminatory local information, which is robust to noise. Both types of features are concatenated to produce more discriminatory feature set. The proposed technique is computationally efficient and gives very good results on JAFFE face database.
  • 关键词:Facial expressions;local ternary pattern;Weber local descriptor;feature level fusion;computationally efficient
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