Are you looking at me?: monitoring classrooms

Detalhes bibliográficos
Autor(a) principal: Canedo, Daniel Duarte
Data de Publicação: 2017
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10773/23483
Resumo: This dissertation implements a monitoring system that can be used in three different contexts: monitoring a single student, monitoring a classroom or monitoring a group of people. In order to build this system, we based the development on the use of algorithms for face detection, face recognition and facial features extraction. During this work it was also implemented an eye tracker, a face tracker, an head estimation pose and emotion detection. For each context, different approaches were developed. For the single user monitoring, there was the need of recognizing the face. For this context, the most convenient algorithm was based on Local Binary Patterns Histograms. After a successful recognition, the system assigns an ID to the face and starts tracking it while retrieving useful data from the facial features. For the classroom monitoring, there was no need of recognition, only face tracking. For each face detected, an ID is assigned and the face tracker starts. For the monitoring of a group of people, there was the need of making a face recognition each time a new face appears in the frame and, after a successful recognition, the face tracker starts. The main contributions of this thesis are an automatic calibration for the digital camera used in the system for a better face recognition, a modular solution separated in three components that can be used to monitor three different contexts, retrieving relevant information during a certain period of time that an individual was in front of the camera. The developed software was integrated in a graphical user interface software provided by the camera manufacturer.
id RCAP_5cbbb45ed8530e149bf0dfa32ca55721
oai_identifier_str oai:ria.ua.pt:10773/23483
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling Are you looking at me?: monitoring classroomsReconhecimento facial (Ciência de computadores)Reconhecimento de padrãoAnálise de imagemEngenharia eletrónicaThis dissertation implements a monitoring system that can be used in three different contexts: monitoring a single student, monitoring a classroom or monitoring a group of people. In order to build this system, we based the development on the use of algorithms for face detection, face recognition and facial features extraction. During this work it was also implemented an eye tracker, a face tracker, an head estimation pose and emotion detection. For each context, different approaches were developed. For the single user monitoring, there was the need of recognizing the face. For this context, the most convenient algorithm was based on Local Binary Patterns Histograms. After a successful recognition, the system assigns an ID to the face and starts tracking it while retrieving useful data from the facial features. For the classroom monitoring, there was no need of recognition, only face tracking. For each face detected, an ID is assigned and the face tracker starts. For the monitoring of a group of people, there was the need of making a face recognition each time a new face appears in the frame and, after a successful recognition, the face tracker starts. The main contributions of this thesis are an automatic calibration for the digital camera used in the system for a better face recognition, a modular solution separated in three components that can be used to monitor three different contexts, retrieving relevant information during a certain period of time that an individual was in front of the camera. The developed software was integrated in a graphical user interface software provided by the camera manufacturer.Esta dissertação implementa um sistema de monitorização que pode ser usado em três contextos diferentes: monitorização de um estudante, monitorização de uma sala de aula ou monitorização de um grupo de pessoas. Por forma a construir este sistema, baseamo-nos no uso de algoritmos para deteção facial, reconhecimento facial e extração de características faciais. Durante este trabalho também foi implementado um tracking do olhar, tracking facial, estimativa da pose da cabeça e deteção de emoções. Para cada contexto, várias abordagens foram desenvolvidas. Para a monitorização de um estudante, foi preciso reconhecer a face. Para este contexto, o algoritmo mais conveniente foi baseado no Local Binary Patterns Histograms. Depois de um reconhecimento bem sucedido, o sistema atribui um ID à face e começa a dar tracking à mesma enquanto recolhe informação útil das características faciais. Para a monitorização de uma sala de aula, não foi preciso reconhecer faces, apenas tracking facial. Para a monitorização de um grupo de pessoas, foi preciso fazer reconhecimento facial de cada vez que aparecesse uma nova face em cena, e depois de um reconhecimento bem sucedido, o tracking facial começa. As principais contribuições desta tese foram uma calibração automática para a câmera digital usada no sistema para um melhor reconhecimento facial, uma solução modular separada em três componentes que podem ser usados para monitorizar três contextos diferentes, recolhendo informação relevante durante um certo período de tempo que certo indivíduo esteve em frente da câmera. O software desenvolvido foi integrado num software gráfico de user interface fornecido pelo fabricante da câmera.Universidade de Aveiro2018-06-13T13:17:07Z2017-01-01T00:00:00Z2017info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10773/23483TID:201938669engCanedo, Daniel Duarteinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-22T11:45:43Zoai:ria.ua.pt:10773/23483Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T02:57:13.494265Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Are you looking at me?: monitoring classrooms
title Are you looking at me?: monitoring classrooms
spellingShingle Are you looking at me?: monitoring classrooms
Canedo, Daniel Duarte
Reconhecimento facial (Ciência de computadores)
Reconhecimento de padrão
Análise de imagem
Engenharia eletrónica
title_short Are you looking at me?: monitoring classrooms
title_full Are you looking at me?: monitoring classrooms
title_fullStr Are you looking at me?: monitoring classrooms
title_full_unstemmed Are you looking at me?: monitoring classrooms
title_sort Are you looking at me?: monitoring classrooms
author Canedo, Daniel Duarte
author_facet Canedo, Daniel Duarte
author_role author
dc.contributor.author.fl_str_mv Canedo, Daniel Duarte
dc.subject.por.fl_str_mv Reconhecimento facial (Ciência de computadores)
Reconhecimento de padrão
Análise de imagem
Engenharia eletrónica
topic Reconhecimento facial (Ciência de computadores)
Reconhecimento de padrão
Análise de imagem
Engenharia eletrónica
description This dissertation implements a monitoring system that can be used in three different contexts: monitoring a single student, monitoring a classroom or monitoring a group of people. In order to build this system, we based the development on the use of algorithms for face detection, face recognition and facial features extraction. During this work it was also implemented an eye tracker, a face tracker, an head estimation pose and emotion detection. For each context, different approaches were developed. For the single user monitoring, there was the need of recognizing the face. For this context, the most convenient algorithm was based on Local Binary Patterns Histograms. After a successful recognition, the system assigns an ID to the face and starts tracking it while retrieving useful data from the facial features. For the classroom monitoring, there was no need of recognition, only face tracking. For each face detected, an ID is assigned and the face tracker starts. For the monitoring of a group of people, there was the need of making a face recognition each time a new face appears in the frame and, after a successful recognition, the face tracker starts. The main contributions of this thesis are an automatic calibration for the digital camera used in the system for a better face recognition, a modular solution separated in three components that can be used to monitor three different contexts, retrieving relevant information during a certain period of time that an individual was in front of the camera. The developed software was integrated in a graphical user interface software provided by the camera manufacturer.
publishDate 2017
dc.date.none.fl_str_mv 2017-01-01T00:00:00Z
2017
2018-06-13T13:17:07Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10773/23483
TID:201938669
url http://hdl.handle.net/10773/23483
identifier_str_mv TID:201938669
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade de Aveiro
publisher.none.fl_str_mv Universidade de Aveiro
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
_version_ 1799137626269155328