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Autors: Neshov, N. N., Draganov, I. R., Manolova, A. H.
Title: Facial Expression Recognition Based on Constrained Local Models and Support Vector Machines
Keywords: Constrained Local Model (CLM), Support Vector Machines (SVM), Expression Recognition (ER), Emotion Estimation, OpenIMAJ

Abstract: This paper presents a face expression recognition algorithm using Constrained Local Model (CLM). CLM is facial alignment method that is based on Active Shape Models (ASM) and Active Appearance Models (AAM). It takes the advantages of both of them and gains high accuracy. To distinguish different expression states, we use CLM model parameters that describe shape deformation in a compact form. These parameters form feature vectors for training Kernel Support Vector Machine (KSVM) classifier. The experimental results over Cohn-Kanade Extended Facial Expression (CK+) database show improvement of the recognition rate in comparison to some existing methods, suggested by other authors.

References

    Issue
    L International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST'2015), vol. 1, issue 1, pp. 58-61, 2015, Bulgaria, ISBN ISBN: 978-619-167-182-3

    Copyright ICEST

    Full text of the publication

    Вид: постер/презентация в международен форум, публикация в реферирано издание, индексирана в Scopus

    Въведена от: гл. ас. д-р Николай Нинков Нешов