A Simple Geometric-Based Descriptor for Facial Expression Recognition

Mostrar todas las versiones(2)

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 these descriptors for...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Acevedo, D., Negri, P., Buemi, M.E., Fernandez, F.G., Mejail, M., 3dMD; Baidu; DI4D; et al.; Mitsubishi Electric Research Laboratories, Inc; NSF
Formato:	CONF
Materias:	Gesture recognition Nearest neighbor search Random processes Conditional random field Dynamic approaches Facial expression recognition Facial Expressions K-nearest neighbors classifiers Non-verbal human Sets of features Training example Face recognition
Acceso en línea:	http://hdl.handle.net/20.500.12110/paper_97815090_v_n_p802_Acevedo
Aporte de:	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

id	todo:paper_97815090_v_n_p802_Acevedo
record_format	dspace
spelling	todo:paper_97815090_v_n_p802_Acevedo2023-10-03T16:43:47Z A Simple Geometric-Based Descriptor for Facial Expression Recognition Acevedo, D. Negri, P. Buemi, M.E. Fernandez, F.G. Mejail, M. 3dMD; Baidu; DI4D; et al.; Mitsubishi Electric Research Laboratories, Inc; NSF Gesture recognition Nearest neighbor search Random processes Conditional random field Dynamic approaches Facial expression recognition Facial Expressions K-nearest neighbors classifiers Non-verbal human Sets of features Training example Face 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 these descriptors for facial expression recognition by means of two different approaches. One is a dynamic approach where recognition is performed by a Conditional Random Field (CRF) classifier. The other approach is 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. An analysis of the most discriminative landmarks for the CRF approach is presented. We compare both methodologies, analyse their similarities and differences. Comparisons with other state-ofthe- art techniques on the CK+ dataset are shown. Even though both methodologies are different from each other, the descriptor remains robust and precise in the recognition of expressions. © 2017 IEEE. CONF info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_97815090_v_n_p802_Acevedo
institution	Universidad de Buenos Aires
institution_str	I-28
repository_str	R-134
collection	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic	Gesture recognition Nearest neighbor search Random processes Conditional random field Dynamic approaches Facial expression recognition Facial Expressions K-nearest neighbors classifiers Non-verbal human Sets of features Training example Face recognition
spellingShingle	Gesture recognition Nearest neighbor search Random processes Conditional random field Dynamic approaches Facial expression recognition Facial Expressions K-nearest neighbors classifiers Non-verbal human Sets of features Training example Face recognition Acevedo, D. Negri, P. Buemi, M.E. Fernandez, F.G. Mejail, M. 3dMD; Baidu; DI4D; et al.; Mitsubishi Electric Research Laboratories, Inc; NSF A Simple Geometric-Based Descriptor for Facial Expression Recognition
topic_facet	Gesture recognition Nearest neighbor search Random processes Conditional random field Dynamic approaches Facial expression recognition Facial Expressions K-nearest neighbors classifiers Non-verbal human Sets of features Training example Face recognition
description	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 these descriptors for facial expression recognition by means of two different approaches. One is a dynamic approach where recognition is performed by a Conditional Random Field (CRF) classifier. The other approach is 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. An analysis of the most discriminative landmarks for the CRF approach is presented. We compare both methodologies, analyse their similarities and differences. Comparisons with other state-ofthe- art techniques on the CK+ dataset are shown. Even though both methodologies are different from each other, the descriptor remains robust and precise in the recognition of expressions. © 2017 IEEE.
format	CONF
author	Acevedo, D. Negri, P. Buemi, M.E. Fernandez, F.G. Mejail, M. 3dMD; Baidu; DI4D; et al.; Mitsubishi Electric Research Laboratories, Inc; NSF
author_facet	Acevedo, D. Negri, P. Buemi, M.E. Fernandez, F.G. Mejail, M. 3dMD; Baidu; DI4D; et al.; Mitsubishi Electric Research Laboratories, Inc; NSF
author_sort	Acevedo, D.
title	A Simple Geometric-Based Descriptor for Facial Expression Recognition
title_short	A Simple Geometric-Based Descriptor for Facial Expression Recognition
title_full	A Simple Geometric-Based Descriptor for Facial Expression Recognition
title_fullStr	A Simple Geometric-Based Descriptor for Facial Expression Recognition
title_full_unstemmed	A Simple Geometric-Based Descriptor for Facial Expression Recognition
title_sort	simple geometric-based descriptor for facial expression recognition
url	http://hdl.handle.net/20.500.12110/paper_97815090_v_n_p802_Acevedo
work_keys_str_mv	AT acevedod asimplegeometricbaseddescriptorforfacialexpressionrecognition AT negrip asimplegeometricbaseddescriptorforfacialexpressionrecognition AT buemime asimplegeometricbaseddescriptorforfacialexpressionrecognition AT fernandezfg asimplegeometricbaseddescriptorforfacialexpressionrecognition AT mejailm asimplegeometricbaseddescriptorforfacialexpressionrecognition AT 3dmdbaidudi4detalmitsubishielectricresearchlaboratoriesincnsf asimplegeometricbaseddescriptorforfacialexpressionrecognition AT acevedod simplegeometricbaseddescriptorforfacialexpressionrecognition AT negrip simplegeometricbaseddescriptorforfacialexpressionrecognition AT buemime simplegeometricbaseddescriptorforfacialexpressionrecognition AT fernandezfg simplegeometricbaseddescriptorforfacialexpressionrecognition AT mejailm simplegeometricbaseddescriptorforfacialexpressionrecognition AT 3dmdbaidudi4detalmitsubishielectricresearchlaboratoriesincnsf simplegeometricbaseddescriptorforfacialexpressionrecognition
_version_	1807317369171738624

A Simple Geometric-Based Descriptor for Facial Expression Recognition

Ejemplares similares