@Article{MariaElenaMeza-de-Luna2016,
author="Maria Elena Meza-de-Luna
and Juan Ramon Terven Salinas
and Bogdan Raducanu
and Joaquin Salas",
title="Assessing the Influence of Mirroring on the Perception of Professional Competence using Wearable Technology",
journal="IEEE Transactions on Affective Computing",
year="2016",
volume="9",
number="2",
pages="161--175",
optkeywords="Mirroring",
optkeywords="Nodding",
optkeywords="Competence",
optkeywords="Perception",
optkeywords="Wearable Technology",
abstract="Nonverbal communication is an intrinsic part in daily face-to-face meetings. A frequently observed behavior during social interactions is mirroring, in which one person tends to mimic the attitude of the counterpart. This paper shows that a computer vision system could be used to predict the perception of competence in dyadic interactions through the automatic detection of mirroringevents. To prove our hypothesis, we developed: (1) A social assistant for mirroring detection, using a wearable device which includes a video camera and (2) an automatic classifier for the perception of competence, using the number of nodding gestures and mirroring events as predictors. For our study, we used a mixed-method approach in an experimental design where 48 participants acting as customers interacted with a confederated psychologist. We found that the number of nods or mirroring events has a significant influence on the perception of competence. Our results suggest that: (1) Customer mirroring is a better predictor than psychologist mirroring; (2) the number of psychologist{\textquoteright}s nods is a better predictor than the number of customer{\textquoteright}s nods; (3) except for the psychologist mirroring, the computer vision algorithm we used worked about equally well whether it was acquiring images from wearable smartglasses or fixed cameras.",
optnote="OR; 600.072;MV",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=2826), last updated on Tue, 25 Oct 2022 09:46:07 +0200",
doi="10.1109/TAFFC.2016.2606594",
file=":http://refbase.cvc.uab.es/files/MTR2016.pdf:PDF"
}