Evolutionary fusion of local texture patterns for facial expression recognition

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@InProceedings{Ahmed:2015:ieeeICIP,
  author =       "Faisal Ahmed and Padma Polash Paul and 
                 Marina L. Gavrilova",
  booktitle =    "2015 IEEE International Conference on Image Processing
                 (ICIP)",
  title =        "Evolutionary fusion of local texture patterns for
                 facial expression recognition",
  year =         "2015",
  pages =        "1031--1035",
  abstract =     "This paper presents a simple, yet effective facial
                 feature descriptor based on evolutionary synthesis of
                 different local texture patterns. Unlike the
                 traditional face descriptors that exploit
                 visually-meaningful facial features, the proposed
                 method adopts a genetic programming-based feature
                 fusion approach that uses different local texture
                 patterns and a set of linear and nonlinear operators in
                 order to synthesise new features. The strength of this
                 approach lies in fusing the advantages of different
                 state-of-the-art local texture descriptors and thus,
                 obtaining more robust composite features. Recognition
                 performance of the proposed method is evaluated using
                 the Cohn-Kanade (CK) and the Japanese female facial
                 expression (JAFFE) database. In our experiments, facial
                 features synthesised based on the proposed approach
                 yield an improved recognition performance, as compared
                 to some well-known face feature descriptors.",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/ICIP.2015.7350956",
  month =        sep,
  notes =        "Also known as \cite{7350956}",
}

Genetic Programming entries for Faisal Ahmed Padma Polash Paul Marina L Gavrilova

Citations