@InProceedings{VictorPonce2013,
author="Victor Ponce
and Sergio Escalera
and Xavier Baro",
title="Multi-modal Social Signal Analysis for Predicting Agreement in Conversation Settings",
booktitle="15th ACM International Conference on Multimodal Interaction",
year="2013",
pages="495--502",
abstract="In this paper we present a non-invasive ambient intelligence framework for the analysis of non-verbal communication applied to conversational settings. In particular, we apply feature extraction techniques to multi-modal audio-RGB-depth data. We compute a set of behavioral indicators that define communicative cues coming from the fields of psychology and observational methodology. We test our methodology over data captured in victim-offender mediation scenarios. Using different state-of-the-art classification approaches, our system achieve upon 75\% of recognition predicting agreement among the parts involved in the conversations, using as ground truth the experts opinions.",
optnote="HuPBA;MV",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=2488), last updated on Thu, 10 Nov 2016 12:25:29 +0100",
isbn="978-1-4503-2129-7",
doi="10.1145/2522848.2532594"
}