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Head motion synchrony and its correlation to affectivity in dyadic interactions
Abstract
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 through the Kullback-Leibler divergence of the GMM posteriors of their respective motion sequences. We use an audiovisual database of distressed couple interactions, extensively annotated by psychologists, to test two hypotheses using the derived similarity measure. We validate the first hypothesis — that people are more likely to increase their degree of synchrony as the interaction progresses — by comparing the first and second halves of the interaction. The second hypothesis tests if the relative change of the similarity measure from these two halves is significantly correlated with the behavioral annotation by the domain experts. This work underscores the importance of head motion as an interaction cue, and the feasibility of using it in a computational model for synchrony behavior.
Figures
Illustration of the processing steps in Sec.3
Illustration of the processing steps in Sec.3
Keywords
Head motion | Synchrony | Behavioral signal processing | Entrainment | Linear prediction | Gaussian mixture model
Authors
Publication Date
2013/07/15
Conference
IEEE International Conference on Multimedia and Expo (ICME)
2013 IEEE International Conference on Multimedia and Expo (ICME)
DOI
10.1109/icme.2013.6607480
Publisher
IEEE Xplore