@Article{EstefaniaTalavera2020,
author="Estefania Talavera
and Carolin Wuerich
and Nicolai Petkov
and Petia Radeva",
title="Topic modelling for routine discovery from egocentric photo-streams",
journal="Pattern Recognition",
year="2020",
volume="104",
pages="107330",
optkeywords="Routine",
optkeywords="Egocentric vision",
optkeywords="Lifestyle",
optkeywords="Behaviour analysis",
optkeywords="Topic modelling",
abstract="Developing tools to understand and visualize lifestyle is of high interest when addressing the improvement of habits and well-being of people. Routine, defined as the usual things that a person does daily, helps describe the individuals{\textquoteright} lifestyle. With this paper, we are the first ones to address the development of novel tools for automatic discovery of routine days of an individual from his/her egocentric images. In the proposed model, sequences of images are firstly characterized by semantic labels detected by pre-trained CNNs. Then, these features are organized in temporal-semantic documents to later be embedded into a topic models space. Finally, Dynamic-Time-Warping and Spectral-Clustering methods are used for final day routine/non-routine discrimination. Moreover, we introduce a new EgoRoutine-dataset, a collection of 104 egocentric days with more than 100.000 images recorded by 7 users. Results show that routine can be discovered and behavioural patterns can be observed.",
optnote="MILAB; no proj",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=3435), last updated on Mon, 24 Oct 2022 17:54:30 +0200",
doi="10.1016/j.patcog.2020.107330",
opturl="https://doi.org/10.1016/j.patcog.2020.107330"
}