A citation k-NN approach for facial expression recognition

The identification of facial expressions with human emotions plays a key role in non-verbal human communication and has applications in several areas. In this work, we propose a descriptor based on areas and angles of triangles formed by the landmarks from face images. We test this descriptors for f...

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Detalles Bibliográficos
Autores principales: Acevedo, D., Negri, P., Buemi, M.E., Gómez Fernández, F., Mejail, M., Velastin S., Mendoza M., Chilean Association of Pattern Recognition; Department of Informatics; Federico Santa Maria
Formato: SER
Materias:
Nearest neighbor search
Pattern recognition
Facial expression recognition
Facial Expressions
Human emotion
K-nearest neighbors classifiers
Non-verbal human
Sets of features
State-of-the-art techniques
Training example
Face recognition
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_03029743_v10657LNCS_n_p1_Acevedo
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
Descripción
Sumario:The identification of facial expressions with human emotions plays a key role in non-verbal human communication and has applications in several areas. In this work, we propose a descriptor based on areas and angles of triangles formed by the landmarks from face images. We test this descriptors for facial expression recognition by means of an adaptation of the k-Nearest Neighbors classifier called Citation-kNN in which the training examples come in the form of sets of feature vectors. Comparisons with other state-of-the-art techniques on the CK+ dataset are shown. The descriptor remains robust and precise in the recognition of expressions. © Springer International Publishing AG, part of Springer Nature 2018.

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