Image analysis using facial symmetry features for the tasks of detection and assessment of facial palsy and gesture recognition in patients

GEMMA SILVANA PARRA DOMÍNGUEZ

Please use this identifier to cite or link to this item: http://repositorio.ugto.mx/handle/20.500.12059/7706

Full metadata record

DC Field	Value	Language
dc.rights.license	http://creativecommons.org/licenses/by-nc-nd/4.0	es_MX
dc.contributor	RAUL ENRIQUE SANCHEZ YAÑEZ	es_MX
dc.creator	GEMMA SILVANA PARRA DOMÍNGUEZ	es_MX
dc.date.accessioned	2023-02-17T19:22:27Z	-
dc.date.available	2023-02-17T19:22:27Z	-
dc.date.issued	2022-08-18	-
dc.identifier.uri	http://repositorio.ugto.mx/handle/20.500.12059/7706	-
dc.language.iso	eng	en
dc.publisher	Universidad de Guanajuato	es_MX
dc.rights	info:eu-repo/semantics/openAccess	es_MX
dc.subject.classification	CIS- Doctorado en Ingeniería Eléctrica	es_MX
dc.title	Image analysis using facial symmetry features for the tasks of detection and assessment of facial palsy and gesture recognition in patients	en
dc.title.alternative	Análisis de imágenes usando propiedades de simetría facial para las tareas de detección y medición del grado de parálisis facial y el reconocimiento de gestos en pacientes	es_MX
dc.type	info:eu-repo/semantics/doctoralThesis	es_MX
dc.creator.id	info:eu-repo/dai/mx/cvu/302076	es_MX
dc.subject.cti	info:eu-repo/classification/cti/7	es_MX
dc.subject.cti	info:eu-repo/classification/cti/33	es_MX
dc.subject.cti	info:eu-repo/classification/cti/3311	es_MX
dc.subject.keywords	Image analysis	en
dc.subject.keywords	Facial symmetry – Features	en
dc.subject.keywords	Facial palsy - Assessment	en
dc.subject.keywords	Gesture recognition	en
dc.subject.keywords	Computer vision techniques	en
dc.contributor.id	info:eu-repo/dai/mx/cvu/30994	es_MX
dc.contributor.role	director	es_MX
dc.type.version	info:eu-repo/semantics/publishedVersion	es_MX
dc.contributor.two	CARLOS HUGO GARCIA CAPULIN	es_MX
dc.contributor.idtwo	info:eu-repo/dai/mx/cvu/41635	es_MX
dc.contributor.roletwo	director	-
dc.description.abstractEnglish	Facial paralysis is a physical condition that negatively affects the facial structure. It is characterized by the incapacity to move some muscles of the face. Different factors can develop facial paralysis, for example, a congenital condition, trauma, disease like stroke, brain tumor, or Bell’s palsy. Since paralysis can affect one or both sides of the face, there is a remarkable drooping of facial movements. Therefore, the patient exhibits difficulty performing daily life activities such as speaking, blinking, swallowing saliva, eating, or communicating through natural facial expressions. Recently, computer-based systems have been designed to automatically diagnose facial paralysis through images. Those systems are essential in developing standardized tools for medical assessment, treatment, and monitoring; additionally, they are expected to provide user-friendly tools for patient monitoring at home. Simultaneously, computed-based systems are also being developed to recognize facial expressions in a wide variety of situations. Facial expressions are crucial in designing security, healthcare, entertainment, advertisement, education, and robotics applications. Performing these recognition tasks in palsy patients could allow their integration in developing and using such applications. This research seeks to diagnose facial palsy in a photograph using computer vision techniques and machine learning algorithms. The analysis of faces is performed in terms of symmetry. Knowing that almost all humans exhibit a level of asymmetry between the left and right sides of the face, it is expected to find a boundary capable of distinguishing between healthy and palsy faces. In other words, this work seeks to characterize human faces by assuming that a healthy face is pretty symmetrical and a palsy face is not.	en
Appears in Collections:	Doctorado en Ingeniería Eléctrica

Files in This Item:

File	Description	Size	Format
GEMMA SILVANA PARRA DOMÍNGUEZ_Tesis24.pdf		5.83 MB	Adobe PDF	View/Open

Show simple item record