@InProceedings{EstefaniaTalavera2019,
author="Estefania Talavera
and Nicolai Petkov
and Petia Radeva",
title="Unsupervised Routine Discovery in Egocentric Photo-Streams",
booktitle="18th International Conference on Computer Analysis of Images and Patterns",
year="2019",
volume="11678",
pages="576--588",
optkeywords="Routine discovery",
optkeywords="Lifestyle",
optkeywords="Egocentric vision",
optkeywords="Behaviour analysis",
abstract="The routine of a person is defined by the occurrence of activities throughout different days, and can directly affect the person{\textquoteright}s health. In this work, we address the recognition of routine related days. To do so, we rely on egocentric images, which are recorded by a wearable camera and allow to monitor the life of the user from a first-person view perspective. We propose an unsupervised model that identifies routine related days, following an outlier detection approach. We test the proposed framework over a total of 72 days in the form of photo-streams covering around 2 weeks of the life of 5 different camera wearers. Our model achieves an average of 76\% Accuracy and 68\% Weighted F-Score for all the users. Thus, we show that our framework is able to recognise routine related days and opens the door to the understanding of the behaviour of people.",
optnote="MILAB; no proj",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=3367), last updated on Tue, 25 Jan 2022 11:32:12 +0100",
doi="10.1007/978-3-030-29888-3_47",
opturl="https://link.springer.com/chapter/10.1007\%2F978-3-030-29888-3_47",
file=":http://refbase.cvc.uab.es/files/TPR2019a.pdf:PDF"
}