Facial expression recognition with dynamic cascaded classifier

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dc.contributor.authorAshir, Abubakar Muhammad
dc.contributor.authorEleyan, Alaa
dc.contributor.authorAkdemir, Bayram
dc.date.accessioned2020-03-26T20:19:54Z
dc.date.available2020-03-26T20:19:54Z
dc.date.issued2019
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractIn this paper, a new approach for facial expression recognition has been proposed. The approach has imbedded a new feature extraction technique, new multiclass classification approach and a new kernel parameter optimization for support vector machines. The scheme of the approach begins with feature extraction from the input vectors, and the extracted features are transformed into a Gaussian space using compressive sensing techniques. This process ensures feature vector dimensionality reduction and matches the features vectors with radial basis function kernel used in support vector machines for classification. Prior to classification, an optimized parameter for support vector machines training is automatically determined based on an approach proposed which relies on the receiver operating characteristics of the support vector machine classifier. With the optimized kernel parameter, new proposed multiclass classification approach is used to finally classify any vector. In all the experiments conducted on the two facial expression databases with different cross-validation techniques, the proposed approach outperforms its counterparts under the same database and settings. The results further confirmed the validity and advantages of the proposed approach over other approaches currently used in the literature. © 2019, Springer-Verlag London Ltd., part of Springer Nature.en_US
dc.identifier.doi10.1007/s00521-019-04138-4en_US
dc.identifier.issn0941-0643en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://dx.doi.org/10.1007/s00521-019-04138-4
dc.identifier.urihttps://hdl.handle.net/20.500.12395/38441
dc.identifier.wosWOS:000529745200069en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Londonen_US
dc.relation.ispartofNeural Computing and Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectCompressive sensingen_US
dc.subjectFacial expression recognitionen_US
dc.subjectRadial basis function kernelen_US
dc.subjectSupport vector machineen_US
dc.titleFacial expression recognition with dynamic cascaded classifieren_US
dc.typeArticleen_US

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