%0 Conference Proceedings
%T Social Relation Recognition in Egocentric Photostreams
%A Emanuel Sanchez Aimar
%A Petia Radeva
%A Mariella Dimiccoli
%B 26th International Conference on Image Processing
%D 2019
%F Emanuel Sanchez Aimar2019
%O MILAB; no menciona
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=3370), last updated on Tue, 25 Jan 2022 11:25:29 +0100
%X 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'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.
%U https://ieeexplore.ieee.org/document/8803634
%U http://refbase.cvc.uab.es/files/SRD2019.pdf
%U http://dx.doi.org/10.1109/ICIP.2019.8803634
%P 3227-3231