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http://hdl.handle.net/10609/92803
Title: | Non-verbal communication analysis in victim-offender mediations |
Author: | Ponce López, Víctor Escalera, Sergio Pérez, Marc Janés, Oriol Baró, Xavier |
Others: | Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3) Universitat Autònoma de Barcelona (UAB) |
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 |
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. |
Keywords: | victim-offender mediation multi-modal human behavior analysis face and gesture recognition social signal processing computer vision machine learning |
DOI: | 10.1016/j.patrec.2015.07.040 |
Document type: | info:eu-repo/semantics/article |
Version: | info:eu-repo/semantics/submittedVersion |
Issue Date: | 19-Jan-2015 |
Publication license: | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Appears in Collections: | Articles cientÍfics Articles |
Files in This Item:
File | Description | Size | Format | |
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nonverbal.pdf | Preprint | 4,23 MB | Adobe PDF | View/Open |
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