@InProceedings{EmanuelSanchezAimar2019,
author="Emanuel Sanchez Aimar
and Petia Radeva
and Mariella Dimiccoli",
title="Social Relation Recognition in Egocentric Photostreams",
booktitle="26th International Conference on Image Processing",
year="2019",
pages="3227--3231",
abstract="This paper proposes an approach to automatically categorize the social interactions of a user wearing a photo-camera (2fpm), by relying solely on what the camera is seeing. The problem is challenging due to the overwhelming complexity of social life and the extreme intra-class variability of social interactions captured under unconstrained conditions. We adopt the formalization proposed in Bugental{\textquoteright}s social theory, that groups human relations into five social domains with related categories. Our method is a new deep learning architecture that exploits the hierarchical structure of the label space and relies on a set of social attributes estimated at frame level to provide a semantic representation of social interactions. Experimental results on the new EgoSocialRelation dataset demonstrate the effectiveness of our proposal.",
optnote="MILAB; no menciona",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=3370), last updated on Tue, 25 Jan 2022 11:25:29 +0100",
doi="10.1109/ICIP.2019.8803634",
opturl="https://ieeexplore.ieee.org/document/8803634",
file=":http://refbase.cvc.uab.es/files/SRD2019.pdf:PDF"
}