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This paper presents a computational study of head motion in human interaction, notably of its role in conveying interlocutors’ behavioral characteristics. Head motion is physically complex and carries rich information; current modeling approaches based on visual signals, however , are still limited in their ability to adequately capture these important properties. Guided by the methodology of kinesics...
Behavioral synchrony, or entrainment, is a phenomenon of great interest to psychologists and a challenging construct to quantify. In this work we study the synchrony behavior of head motion in human dyadic interactions. We model head motion using Gaussian Mixture Model (GMM) of line spectral frequencies extracted from the motion vectors of the head. We quantify interlocutor head motion similarity...
Emotion expression is an essential part of human interaction. Rich emotional information is conveyed through the human face. In this study, we analyze detailed motion-captured facial information of ten speakers of both genders during emotional speech. We derive compact facial representations using methods motivated by Principal Component Analysis and speaker face normalization. Moreover, we model...
Emotion expression associated with human communication is known to be a multimodal process. In this work, we investigate the way that emotional information is conveyed by facial and vocal modalities, and how these modalities can be effectively combined to achieve improved emotion recognition accuracy. In particular, the behaviors of different facial regions are studied in detail. We analyze an emotion...
Expressive audio-visual synthetic characters are increasingly employed in research and commercial applications. However, the mechanism that people employ to interpret conflicting or uncertain multimodal emotional displays of these agents is not yet well understood. This study is an attempt to provide a better understanding of the interpretation of conflicting expressive displays in video and audio...
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