@Article{JuanRamonTervenSalinas2016,
author="Juan Ramon Terven Salinas
and Bogdan Raducanu
and Maria Elena Meza-de-Luna
and Joaquin Salas",
title="Head-gestures mirroring detection in dyadic social linteractions with computer vision-based wearable devices",
journal="Neurocomputing",
year="2016",
volume="175",
number="B",
pages="866--876",
optkeywords="Head gestures recognition",
optkeywords="Mirroring detection",
optkeywords="Dyadic social interaction analysis",
optkeywords="Wearable devices",
abstract="During face-to-face human interaction, nonverbal communication plays a fundamental role. A relevant aspect that takes part during social interactions is represented by mirroring, in which a person tends to mimic the non-verbal behavior (head and body gestures, vocal prosody, etc.) of the counterpart. In this paper, we introduce a computer vision-based system to detect mirroring in dyadic social interactions with the use of a wearable platform. In our context, mirroring is inferred as simultaneous head noddings displayed by the interlocutors. Our approach consists of the following steps: (1) facial features extraction; (2) facial features stabilization; (3) head nodding recognition; and (4) mirroring detection. Our system achieves a mirroring detection accuracy of 72\% on a custom mirroring dataset.",
optnote="LAMP; 600.072; 600.068;",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=2721), last updated on Mon, 15 Jul 2024 11:48:06 +0200",
doi="10.1016/j.neucom.2015.05.131",
file=":http://refbase.cvc.uab.es/files/TRM2016.pdf:PDF"
}