Short Research Advanced Project: Development of Strategies for Automatic Facial Feature Extraction and Emotion Recognition

dc.contributor.authorRestrepo, David
dc.contributor.authorGomez, Alejandro
dc.contributor.departmentUniversidad EAFIT. Departamento de Cienciasspa
dc.contributor.researchgroupModelado Matemáticospa
dc.creatorRestrepo, David
dc.creatorGomez, Alejandro
dc.date.accessioned2021-04-12T14:11:49Z
dc.date.available2021-04-12T14:11:49Z
dc.date.issued2017-10-18
dc.description.abstractEmotions are a fundamental part of the personal and social skills of the human being. The behavior, intelligence, reason and decision making process are some of the topic that can be influenced by the emotional state of a person. In this paper we develop a computational way for emotion recognition though images using the Cohn-Kanade database to train a pattern recognition neural network and Viola Jones object detector to extract the information of the facial expression. The resulting neural network showed an overall accuracy of 90.7% in recognizing between 6 basic emotions such a surprise, fear, happiness, sadness, disgust and anger.eng
dc.identifierhttps://eafit.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=7035
dc.identifier.isbn9781538603987
dc.identifier.otherWOS;000427290700035
dc.identifier.urihttp://hdl.handle.net/10784/27900
dc.language.isoengeng
dc.publisherIEEE
dc.rightsIEEE
dc.source2017 Ieee 3rd Colombian Conference On Automatic Control (ccac)
dc.subject.keywordComputer Visioneng
dc.subject.keywordEmotion detectioneng
dc.subject.keywordFACSeng
dc.subject.keywordNeural networkeng
dc.subject.keywordPattern recognitioneng
dc.subject.keywordViola Joneseng
dc.titleShort Research Advanced Project: Development of Strategies for Automatic Facial Feature Extraction and Emotion Recognitioneng
dc.typeinfo:eu-repo/semantics/conferencePapereng
dc.typeconferencePapereng
dc.typeinfo:eu-repo/semantics/publishedVersioneng
dc.typepublishedVersioneng
dc.type.localDocumento de conferenciaspa

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