Lifestyle Understanding through the Analysis of Egocentric Photo-streams

Programa de Doctorat en Matemàtica i Informàtica / Tesi realitzada conjuntament amb la Universitat de Groningen

Detalles Bibliográficos
Autor: Talavera Martínez, Estefanía
Tipo de recurso: tesis doctoral
Estado:Versión publicada
Fecha de publicación:2020
País:España
Institución:CBUC, CESCA
Repositorio:TDR. Tesis Doctorales en Red
OAI Identifier:oai:www.tdx.cat:10803/675926
Acceso en línea:http://hdl.handle.net/10803/675926
Access Level:acceso abierto
Palabra clave:Visió per ordinador
Visión por ordenador
Computer vision
Interès personal
Interés personal
Self-interest
"Lifelogging"
Ciències Experimentals i Matemàtiques
62
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network_name_str España
repository_id_str
dc.title.none.fl_str_mv Lifestyle Understanding through the Analysis of Egocentric Photo-streams
title Lifestyle Understanding through the Analysis of Egocentric Photo-streams
spellingShingle Lifestyle Understanding through the Analysis of Egocentric Photo-streams
Talavera Martínez, Estefanía
Visió per ordinador
Visión por ordenador
Computer vision
Interès personal
Interés personal
Self-interest
"Lifelogging"
Ciències Experimentals i Matemàtiques
62
title_short Lifestyle Understanding through the Analysis of Egocentric Photo-streams
title_full Lifestyle Understanding through the Analysis of Egocentric Photo-streams
title_fullStr Lifestyle Understanding through the Analysis of Egocentric Photo-streams
title_full_unstemmed Lifestyle Understanding through the Analysis of Egocentric Photo-streams
title_sort Lifestyle Understanding through the Analysis of Egocentric Photo-streams
dc.creator.none.fl_str_mv Talavera Martínez, Estefanía
author Talavera Martínez, Estefanía
author_facet Talavera Martínez, Estefanía
author_role author
dc.contributor.none.fl_str_mv Radeva, Petia
Petkov, Nicolai
Universitat de Barcelona. Departament de Matemàtiques i Informàtica
dc.subject.none.fl_str_mv Visió per ordinador
Visión por ordenador
Computer vision
Interès personal
Interés personal
Self-interest
"Lifelogging"
Ciències Experimentals i Matemàtiques
62
topic Visió per ordinador
Visión por ordenador
Computer vision
Interès personal
Interés personal
Self-interest
"Lifelogging"
Ciències Experimentals i Matemàtiques
62
description Programa de Doctorat en Matemàtica i Informàtica / Tesi realitzada conjuntament amb la Universitat de Groningen
publishDate 2020
dc.date.none.fl_str_mv 2020
2022
2022
dc.type.none.fl_str_mv info:eu-repo/semantics/doctoralThesis
info:eu-repo/semantics/publishedVersion
format doctoralThesis
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10803/675926
url http://hdl.handle.net/10803/675926
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 174 p.
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Universitat de Barcelona
publisher.none.fl_str_mv Universitat de Barcelona
dc.source.none.fl_str_mv TDX (Tesis Doctorals en Xarxa)
reponame:TDR. Tesis Doctorales en Red
instname:CBUC, CESCA
instname_str CBUC, CESCA
reponame_str TDR. Tesis Doctorales en Red
collection TDR. Tesis Doctorales en Red
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869403483977809920
spelling Lifestyle Understanding through the Analysis of Egocentric Photo-streamsTalavera Martínez, EstefaníaVisió per ordinadorVisión por ordenadorComputer visionInterès personalInterés personalSelf-interest"Lifelogging"Ciències Experimentals i Matemàtiques62Programa de Doctorat en Matemàtica i Informàtica / Tesi realitzada conjuntament amb la Universitat de GroningenDescribing people’s lives has become a hot topic in several disciplines. Lifelogging appeared in the 1960s as the process of recording and tracking personal activity data generated by the daily behaviour of a person. The development of new wearable technologies allows to auto- matically record data from our daily living. Wearable devices are light-ware and affordable, which shows potential for the increase of their use by our society. Egocentric images are recorded by wearable cameras and show a first-person view of the life of the camera wearer. These collected images show an objective view of the daily life of a person and thus are a rich source of information about her or his habits. However, there is lack of tools for the analysis of collections of egocentric photo-sequences and thus room for progress. This thesis investigates the development of automatic tools for the analysis of egocentric images with the ultimate goal of getting understanding of the lifestyle of the camera wearer. This work addresses five main topics in the field of egocentric vision: 1. Temporal photo-sequences segmentation: We introduce an automatic model for the defi- nition of temporal boundaries for the division of egocentric photo-sequences into mo- ments, which are sequences of images describing the same environment. The model is based on global and semantic features and achieves a 66% F-score over the EDUB-Seg dataset. 2. Routine discovery: We propose an automatic tool for the discovery of routine-related days and the visualization of patterns of behaviour, based on the use of topic modelling over semantic concepts extracted from the photo-sequences. The introduction of the EgoRoutine dataset composed of a total of 104 days is part of this work. The model is able to classify days into routine and non-routine related with an accuracy of 80%. 3. Food-related scenes recognition: We introduce a hierarchical classifier for the recognition of visually highly similar food-related images into 15 different classes that describe daily activities related to food consumption, acquisition, and preparation. We intro- duce the EgoFoodScenes dataset, which our model is able to classify into the 15 cate- gories with an accuracy of 68%. 4. Sentiment retrieval: We explore the sentiment associated with images by classifying them into Positive, Neutral, and Negative. Our model is based on the analysis of global features and obtained semantic concepts with associated sentiment. We obtain an ac- curacy of 75%. Results show that positive images relate to outdoor environments or with social interactions, neutral to work-related environments, and negative to non- informative or visually not clear images . 5. Social pattern characterization: We propose a model that characterizes the social be- haviour of the camera wearer based on the occurrence of people that the camera wearer meets throughout her/his data collection. The proposed social parameters allow the definition of a radar chart that shows its potential for the comparison of social patterns among individuals. The introduced and made publicly available egocentric datasets and the obtained results in the different performed experiments indicate that behaviour can be identified and studied. We conclude that the developed automatic algorithms for the analysis of egocentric images allow a better understanding of the lifestyle of the camera wearer. Applications based on the analysis of this data can lead to the improvement of the quality of life of people and therefore, are worth to continue exploring.Universitat de BarcelonaRadeva, PetiaPetkov, NicolaiUniversitat de Barcelona. Departament de Matemàtiques i Informàtica202220222020info:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/publishedVersion174 p.application/pdfapplication/pdfhttp://hdl.handle.net/10803/675926TDX (Tesis Doctorals en Xarxa)reponame:TDR. Tesis Doctorales en Redinstname:CBUC, CESCAInglésADVERTIMENT. Tots els drets reservats. L'accés als continguts d'aquesta tesi doctoral i la seva utilització ha de respectar els drets de la persona autora. Pot ser utilitzada per a consulta o estudi personal, així com en activitats o materials d'investigació i docència en els termes establerts a l'art. 32 del Text Refós de la Llei de Propietat Intel·lectual (RDL 1/1996). Per altres utilitzacions es requereix l'autorització prèvia i expressa de la persona autora. En qualsevol cas, en la utilització dels seus continguts caldrà indicar de forma clara el nom i cognoms de la persona autora i el títol de la tesi doctoral. No s'autoritza la seva reproducció o altres formes d'explotació efectuades amb finalitats de lucre ni la seva comunicació pública des d'un lloc aliè al servei TDX. Tampoc s'autoritza la presentació del seu contingut en una finestra o marc aliè a TDX (framing). Aquesta reserva de drets afecta tant als continguts de la tesi com als seus resums i índexs.info:eu-repo/semantics/openAccessoai:www.tdx.cat:10803/6759262026-06-14T12:46:07Z
score 15,30478

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