Recognition of Facial Expressions using Local Mean Binary Pattern

In this paper, we propose a novel appearance based local feature extraction technique called Local Mean Binary Pattern (LMBP), which efficiently encodes the local texture and global shape of the face. LMBP code is produced by weighting the thresholded neighbor intensity values with respect to mean o...

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Detalles Bibliográficos
Autores: Goyani, Mahesh M., Patel, Narendra
Tipo de recurso: artículo
Fecha de publicación:2017
País:España
Institución:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:ddd.uab.cat:176404
Acceso en línea:https://ddd.uab.cat/record/176404
https://dx.doi.org/urn:doi:10.5565/rev/elcvia.1058
Access Level:acceso abierto
Palabra clave:Local binary pattern
Local mean binary pattern
Local direction pattern
Histogram normalized absolute difference
Support vector machine
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spelling Recognition of Facial Expressions using Local Mean Binary PatternGoyani, Mahesh M.Patel, NarendraLocal binary patternLocal mean binary patternLocal direction patternHistogram normalized absolute differenceSupport vector machineIn this paper, we propose a novel appearance based local feature extraction technique called Local Mean Binary Pattern (LMBP), which efficiently encodes the local texture and global shape of the face. LMBP code is produced by weighting the thresholded neighbor intensity values with respect to mean of 3 x 3 patch. LMBP produces highly discriminative code compared to other state of the art methods. The micro pattern is derived using the mean of the patch, and hence it is robust against illumination and noise variations. An image is divided into M x N regions and feature descriptor is derived by concatenating LMBP distribution of each region. We also propose a novel template matching strategy called Histogram Normalized Absolute Difference (HNAD) for comparing LMBP histograms. Rigorous experiments prove the effectiveness and robustness of LMBP operator. Experiments also prove the superiority of HNAD measure over well-known template matching methods such as L2 norm and Chi-Square measure. We also investigated LMBP for facial expression recognition low resolution. The performance of the proposed approach is tested on well-known datasets CK, JAFFE, and TFEID. 22017-01-0120172017-01-01Articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://ddd.uab.cat/record/176404https://dx.doi.org/urn:doi:10.5565/rev/elcvia.1058reponame:Dipòsit Digital de Documents de la UABinstname:Universitat Autònoma de BarcelonaInglésengopen accesshttp://purl.org/coar/access_right/c_abf2Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.https://creativecommons.org/licenses/by-nc-nd/3.0/info:eu-repo/semantics/openAccessoai:ddd.uab.cat:1764042026-06-06T12:50:31Z
dc.title.none.fl_str_mv Recognition of Facial Expressions using Local Mean Binary Pattern
title Recognition of Facial Expressions using Local Mean Binary Pattern
spellingShingle Recognition of Facial Expressions using Local Mean Binary Pattern
Goyani, Mahesh M.
Local binary pattern
Local mean binary pattern
Local direction pattern
Histogram normalized absolute difference
Support vector machine
title_short Recognition of Facial Expressions using Local Mean Binary Pattern
title_full Recognition of Facial Expressions using Local Mean Binary Pattern
title_fullStr Recognition of Facial Expressions using Local Mean Binary Pattern
title_full_unstemmed Recognition of Facial Expressions using Local Mean Binary Pattern
title_sort Recognition of Facial Expressions using Local Mean Binary Pattern
dc.creator.none.fl_str_mv Goyani, Mahesh M.
Patel, Narendra
author Goyani, Mahesh M.
author_facet Goyani, Mahesh M.
Patel, Narendra
author_role author
author2 Patel, Narendra
author2_role author
dc.subject.none.fl_str_mv Local binary pattern
Local mean binary pattern
Local direction pattern
Histogram normalized absolute difference
Support vector machine
topic Local binary pattern
Local mean binary pattern
Local direction pattern
Histogram normalized absolute difference
Support vector machine
description In this paper, we propose a novel appearance based local feature extraction technique called Local Mean Binary Pattern (LMBP), which efficiently encodes the local texture and global shape of the face. LMBP code is produced by weighting the thresholded neighbor intensity values with respect to mean of 3 x 3 patch. LMBP produces highly discriminative code compared to other state of the art methods. The micro pattern is derived using the mean of the patch, and hence it is robust against illumination and noise variations. An image is divided into M x N regions and feature descriptor is derived by concatenating LMBP distribution of each region. We also propose a novel template matching strategy called Histogram Normalized Absolute Difference (HNAD) for comparing LMBP histograms. Rigorous experiments prove the effectiveness and robustness of LMBP operator. Experiments also prove the superiority of HNAD measure over well-known template matching methods such as L2 norm and Chi-Square measure. We also investigated LMBP for facial expression recognition low resolution. The performance of the proposed approach is tested on well-known datasets CK, JAFFE, and TFEID.
publishDate 2017
dc.date.none.fl_str_mv 2
2017-01-01
2017
2017-01-01
dc.type.none.fl_str_mv Article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://ddd.uab.cat/record/176404
https://dx.doi.org/urn:doi:10.5565/rev/elcvia.1058
url https://ddd.uab.cat/record/176404
https://dx.doi.org/urn:doi:10.5565/rev/elcvia.1058
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
https://creativecommons.org/licenses/by-nc-nd/3.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
https://creativecommons.org/licenses/by-nc-nd/3.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Dipòsit Digital de Documents de la UAB
instname:Universitat Autònoma de Barcelona
instname_str Universitat Autònoma de Barcelona
reponame_str Dipòsit Digital de Documents de la UAB
collection Dipòsit Digital de Documents de la UAB
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