Kyriaki Kalimeri

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In order to predict the Extraversion personality trait, we exploit medium-grained behaviors enacted in group meetings, namely, speaking time and social attention (social gaze). The latter will be further distinguished in to <i>attention given</i> to the group members and <i>attention received</i> from them. The results of our work confirm many of our(More)
—This paper presents the SocioMetric Badges Corpus, a new corpus for social interaction studies collected during a 6 weeks contiguous period in a research institution, monitoring the activity of 53 people. The design of the corpus was inspired by the need to provide researchers and practitioners with: a) raw digital trace data that could be used to directly(More)
This paper presents a multimodal framework employing eye-gaze, head-pose and speech cues to explain observed social attention patterns in meeting scenes. We first investigate a few hypotheses concerning social attention and characterize meetings and individuals based on ground-truth data. This is followed by replication of ground-truth results through(More)
In this paper we modeled the effects that dominant people might induce on the nonverbal behavior (speech energy and body motion) of the other meeting participants using Granger causality technique. Our initial hypothesis that more dominant people have generalized higher influence was not validated when using the DOME-AMI corpus as data source. However, from(More)
Recent studies in social and personality psychology introduced the notion of personality states conceived as concrete behaviors that can be described as having the same contents as traits. Our paper is a first step towards addressing automatically this new perspective. In particular, we will focus on the classification of excerpts of social behavior into(More)
While our daily activities usually involve interactions with others, the current methods on activity recognition do not often exploit the relationship between social interactions and human activity. This paper addresses the problem of interpreting social activity from human interactions captured by mobile sensing networks. Our first goal is to discover(More)