TY  - CONF
AU  - Victor Ponce
AU  - Sergio Escalera
AU  - Xavier Baro
A2  - ICMI
PY  - 2013//
TI  - Multi-modal Social Signal Analysis for Predicting Agreement in Conversation Settings
BT  - 15th ACM International Conference on Multimodal Interaction
SP  - 495
EP  - 502
N2  - 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.
SN  - 978-1-4503-2129-7
UR  - http://dx.doi.org/10.1145/2522848.2532594
N1  - HuPBA;MV
ID  - Victor Ponce2013
ER  -