Non-verbal communication analysis in Victim-Offender Mediations

Víctor Ponce-López, Sergio Escalera, Marc Pérez, Oriol Janés, Xavier Baró

    Research output: Contribution to journalArticleResearchpeer-review

    7 Citations (Scopus)


    © 2015 Elsevier B.V.All rights reserved. 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.
    Original languageEnglish
    Pages (from-to)19-27
    JournalPattern Recognition Letters
    Publication statusPublished - 1 Dec 2015


    • Computer vision
    • Face and gesture recognition
    • Machine learning
    • Multi-modal human behavior analysis
    • Social signal processing
    • Victim-Offender Mediation


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