Behaviour understanding through the analysis of image sequences collected by wearable cameras
Talavera Martínez, Estefanía (University of Groningen. Johann Bernoulli Institute for Mathematics and Computer Science)

Data:	2020
Resum:	Describing people's lifestyle has become a hot topic in the field of artificial intelligence. Lifelogging is described as the process of collecting personal activity data describing the daily behaviour of a person. Nowadays, the development of new technologies and the increasing use of wearable sensors allow to automatically record data from our daily living. In this paper, we describe our developed automatic tools for the analysis of collected visual data that describes the daily behaviour of a person. For this analysis, we rely on sequences of images collected by wearable cameras, which are called egocentric photo-streams. These images are a rich source of information about the behaviour of the camera wearer since they show an objective and first-person view of his or her lifestyle.
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Computer vision ; Egocentric vision ; Lifelogging ; Temporal segmentation ; Behaviour understanding ; Lifestyle tracking ; Food-scenes classification ; Sentiment retrieval ; Social patterns ; Visual pattern recognition ; Scene understanding
Publicat a:	ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 19 Núm. 2 (2020) , p. 1-4 (Special Issue on Recent PhD Thesis Dissemination (2020)) , ISSN 1577-5097

Adreça original: https://elcvia.cvc.uab.es/article/view/v19-n2-Mart%C3%ADnez
Adreça alternativa: https://raco.cat/index.php/ELCVIA/article/view/378780
DOI: 10.5565/rev/elcvia.1240

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