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  • 标题:Robust Facial Expression Recognition via Sparse Representation and Multiple Gabor filters
  • 本地全文:下载
  • 作者:Rania Salah El-Sayed ; Prof.Dr. Ahmed El Kholy ; Prof.Dr. Mohamed Youssri El-Nahas
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2013
  • 卷号:4
  • 期号:3
  • DOI:10.14569/IJACSA.2013.040314
  • 出版社:Science and Information Society (SAI)
  • 摘要:Facial expressions recognition plays important role in human communication. It has become one of the most challenging tasks in the pattern recognition field. It has many applications such as: human computer interaction, video surveillance, forensic applications, criminal investigations, and in many other fields. In this paper we propose a method for facial expression recognition (FER). This method provides new insights into two issues in FER: feature extraction and robustness. For feature extraction we are using sparse representation approach after applying multiple Gabor filter and then using support vector machine (SVM) as classifier. We conduct extensive experiments on standard facial expressions database to verify the performance of proposed method. And we compare the result with other approach.
  • 关键词:thesai; IJACSA; thesai.org; journal; IJACSA papers; Facial expression recognition (FER); L1-minimization; sparse representation; Gabor filters; support vector machine (SVM).
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