Facial expression recognition: A comparison between static and dynamic approaches

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 analyze two approaches for expression recognition. One of them is a staticbased appearance method. In this approach, a binary-based...

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Detalles Bibliográficos
Autores principales:	Buemi, María Elena, Acevedo, Daniel G., Mejail, Marta Estela
Publicado:	2016
Materias:	Conditional random field Facial expressions classification ORB descriptor Pattern recognition Pattern recognition systems Random processes Descriptors Expression recognition Facial expression recognition Facial expressions classifications Oriented fast and rotated brief (ORB) Static and dynamic approach Texture information Face recognition
Acceso en línea:	https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_NIS16339_v2016_n2_p_Iglesias http://hdl.handle.net/20.500.12110/paper_NIS16339_v2016_n2_p_Iglesias
Aporte de:	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

id	paper:paper_NIS16339_v2016_n2_p_Iglesias
record_format	dspace
spelling	paper:paper_NIS16339_v2016_n2_p_Iglesias2023-06-08T16:39:38Z Facial expression recognition: A comparison between static and dynamic approaches Buemi, María Elena Acevedo, Daniel G. Mejail, Marta Estela Conditional random field Facial expressions classification ORB descriptor Pattern recognition Pattern recognition systems Random processes Conditional random field Descriptors Expression recognition Facial expression recognition Facial expressions classifications Oriented fast and rotated brief (ORB) Static and dynamic approach Texture information 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 analyze two approaches for expression recognition. One of them is a staticbased appearance method. In this approach, a binary-based descriptor, denominated Oriented Fast and Rotated BRIEF (ORB), is used on a single frame of a sequence of images to extract texture information, and classified with a Support Vector Machine. The other is a dynamic approach introducing a new simple descriptor based on the angles formed by the landmarks to capture the dynamic of the gesture on an image sequence. In this case the recognition is performed by a Conditional Random Field (CRF) classifier. The paper compares both methodologies, analyze their similarities and differences. Fil:Buemi, M.E. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Acevedo, D. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Mejail, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 2016 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_NIS16339_v2016_n2_p_Iglesias http://hdl.handle.net/20.500.12110/paper_NIS16339_v2016_n2_p_Iglesias
institution	Universidad de Buenos Aires
institution_str	I-28
repository_str	R-134
collection	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic	Conditional random field Facial expressions classification ORB descriptor Pattern recognition Pattern recognition systems Random processes Conditional random field Descriptors Expression recognition Facial expression recognition Facial expressions classifications Oriented fast and rotated brief (ORB) Static and dynamic approach Texture information Face recognition
spellingShingle	Conditional random field Facial expressions classification ORB descriptor Pattern recognition Pattern recognition systems Random processes Conditional random field Descriptors Expression recognition Facial expression recognition Facial expressions classifications Oriented fast and rotated brief (ORB) Static and dynamic approach Texture information Face recognition Buemi, María Elena Acevedo, Daniel G. Mejail, Marta Estela Facial expression recognition: A comparison between static and dynamic approaches
topic_facet	Conditional random field Facial expressions classification ORB descriptor Pattern recognition Pattern recognition systems Random processes Conditional random field Descriptors Expression recognition Facial expression recognition Facial expressions classifications Oriented fast and rotated brief (ORB) Static and dynamic approach Texture information 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 analyze two approaches for expression recognition. One of them is a staticbased appearance method. In this approach, a binary-based descriptor, denominated Oriented Fast and Rotated BRIEF (ORB), is used on a single frame of a sequence of images to extract texture information, and classified with a Support Vector Machine. The other is a dynamic approach introducing a new simple descriptor based on the angles formed by the landmarks to capture the dynamic of the gesture on an image sequence. In this case the recognition is performed by a Conditional Random Field (CRF) classifier. The paper compares both methodologies, analyze their similarities and differences.
author	Buemi, María Elena Acevedo, Daniel G. Mejail, Marta Estela
author_facet	Buemi, María Elena Acevedo, Daniel G. Mejail, Marta Estela
author_sort	Buemi, María Elena
title	Facial expression recognition: A comparison between static and dynamic approaches
title_short	Facial expression recognition: A comparison between static and dynamic approaches
title_full	Facial expression recognition: A comparison between static and dynamic approaches
title_fullStr	Facial expression recognition: A comparison between static and dynamic approaches
title_full_unstemmed	Facial expression recognition: A comparison between static and dynamic approaches
title_sort	facial expression recognition: a comparison between static and dynamic approaches
publishDate	2016
url	https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_NIS16339_v2016_n2_p_Iglesias http://hdl.handle.net/20.500.12110/paper_NIS16339_v2016_n2_p_Iglesias
work_keys_str_mv	AT buemimariaelena facialexpressionrecognitionacomparisonbetweenstaticanddynamicapproaches AT acevedodanielg facialexpressionrecognitionacomparisonbetweenstaticanddynamicapproaches AT mejailmartaestela facialexpressionrecognitionacomparisonbetweenstaticanddynamicapproaches
_version_	1769175823540027392

Facial expression recognition: A comparison between static and dynamic approaches

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