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http://hdl.handle.net/10609/92803
Title: Non-verbal communication analysis in victim-offender mediations
Author: Ponce López, Víctor  
Escalera Guerrero, Sergio
Pérez, Marc
Janés, Oriol
Baró Solé, Xavier  
Others: Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3)
Universitat Autònoma de Barcelona
Keywords: victim-offender mediation
multi-modal human behavior analysis
face and gesture recognition
social signal processing
computer vision
machine learning
Issue Date: 19-Jan-2015
Publisher: Pattern Recognition Letters
Citation: Ponce-López, V., Escalera, S., Pérez, M., Janés, O. & Baró, X. (2015). Non-verbal communication analysis in victim-offender mediations. Pattern Recognition Letters, 67(1), 19-27. doi: 10.1016/j.patrec.2015.07.040
Also see: http://arxiv.org/pdf/1412.2122
Abstract: We present a non-invasive ambient intelligence framework for the semi-automatic analysis of non-verbal communication applied to the restorative justice field. We propose the use of computer vision and social signal processing technologies in real scenarios of Victim-Offender Mediations, applying feature extraction techniques to multi-modal audio-RGB-depth data. We compute a set of behavioral indicators that define communicative cues from the fields of psychology and observational methodology. We test our methodology on data captured in real Victim-Offender Mediation sessions in Catalonia. We define the ground truth based on expert opinions when annotating the observed social responses. Using different state of the art binary classification approaches, our system achieves recognition accuracies of 86% when predicting satisfaction, and 79% when predicting both agreement and receptivity. Applying a regression strategy, we obtain a mean deviation for the predictions between 0.5 and 0.7 in the range [1-5] for the computed social signals.
Language: English
URI: http://hdl.handle.net/10609/92803
ISSN: 0167-8655MIAR
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