An automatic emotion recognition system that uses the human body posture

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dc.contributor.advisorTicona Herrera, Regina Paola
dc.contributor.authorHeredia Parillo, Juanpablo Andrew
dc.date.accessioned2021-04-05T01:23:00Z
dc.date.available2021-04-05T01:23:00Z
dc.date.issued2021
dc.description.abstractNon-verbal communication is very present in our lives, but it can be interpreted in different ways according to many factors. With nonverbal gestures people can express explicit and implicit messages, which makes them important to understand. Computer vision methods for recognising body gestures and machine learning classification methods offer an opportunity to understand what people express with their bodies. This research work focuses on the emotions expressed by body gestures, particularly the posture. Thus, an automatic emotion recognition system from images is proposed, which uses a graph convolutional neural network to perform the classification. Generally, deep learning approach needs many training samples, but these are difficult to obtain for posture emotion recognition, thus, the proposed model trains under a meta-learning algorithm based on the “agnostic model”, which allows training with few examples. Only the meta-learning algorithm was tested, which demonstrated the adaptability and expands the applicability of the graph convolutional neural networks. es_PE
dc.description.uriTrabajo de investigaciónes_PE
dc.formatapplication/pdfes_PE
dc.identifier.other1073106
dc.identifier.urihttps://hdl.handle.net/20.500.12590/16702
dc.language.isoenges_PE
dc.publisherUniversidad Católica San Pabloes_PE
dc.publisher.countryPEes_PE
dc.rightsinfo:eu-repo/semantics/openAccesses_PE
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/es_PE
dc.sourceUniversidad Católica San Pabloes_PE
dc.sourceRepositorio Institucional - UCSPes_PE
dc.subjectEmotion recognition es_PE
dc.subjectPosture Classificationes_PE
dc.subjectMeta-learninges_PE
dc.subject.ocdehttp://purl.org/pe-repo/ocde/ford#1.02.01es_PE
dc.titleAn automatic emotion recognition system that uses the human body posturees_PE
dc.typeinfo:eu-repo/semantics/bachelorThesis
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_PE
renati.advisor.dni40207170
renati.advisor.orcidhttps://orcid.org/0000-0002-2605-5718es_PE
renati.author.dni75151804
renati.discipline611016es_PE
renati.jurorRensso Victor Hugo Mora Colquees_PE
renati.jurorAna Maria Cuadros Valdiviaes_PE
renati.levelhttps://purl.org/pe-repo/renati/level#bachiller
renati.typehttps://purl.org/pe-repo/renati/type#trabajoDeInvestigacion
thesis.degree.disciplineCiencia de la Computaciónes_PE
thesis.degree.grantorUniversidad Católica San Pablo. Departamento de Ciencia de la Computaciónes_PE
thesis.degree.levelBachilleres_PE
thesis.degree.nameBachiller en Ciencia de la Computaciónes_PE
thesis.degree.programPrograma Profesional de Ciencia de la Computaciónes_PE
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