Head-gestures mirroring detection in dyadic social interactions with computer vision-based wearable devices

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• 作者：Juan R. Terven^a ; ^d ; ^{j.r.terven@ieee.org" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Bogdan Raducanu^b ; ^{bogdan@cvc.uab.es" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Marí ; a Elena Meza-de-Luna^c ; ^{mezamariel@gmail.com" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Joaquí ; n Salas^a ; ^{jsalasr@ipn.mx" class="auth_mail" title="E-mail the corresponding author}Author Vitae
• 关键词：Head gestures recognition ; Mirroring detection ; Dyadic social interaction analysis ; Wearable devices
• 刊名：Neurocomputing
• 出版年：2016
• 出版时间：29 January 2016
• 年：2016
• 卷：175
• 期：part_PB
• 页码：866-876
• 全文大小：1839 K

文摘

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.