Title
Modeling head motion entrainment for prediction of couples' behavioral characteristics
Abstract
Our work examines the link between head motion entrainment of interacting couples and human expert's judgment on certain overall behavioral characteristics (e.g., Blame patterns). We employ a data-driven model that clusters head motion in an unsupervised manner into elementary types called kinemes. We propose three groups of similarity measures based on Kullback-Leibler divergence to model entrainment. We find that the divergence of the (joint) distribution of kinemes yields consistent and significant correlation with target behavior characteristics. The divergence of the conditional distribution of kinemes is shown to predict the polarity of the behavioral characteristics. We partly explain the strong correlations via associating the conditional distributions with the prominent behavioral implications of their respective associated kinemes. These results show the possibility of inferring human behavioral characteristics through the modeling of dyadic head motion entrainment.
Year
DOI
Venue
2015
10.1109/ACII.2015.7344556
ACII
Keywords
Field
DocType
Head motion, Entrainment, Kineme, Similarity, Behavioral characteristics
Divergence,Conditional probability distribution,Communication,Computer science,Correlation,Medical treatment,Entrainment (chronobiology)
Conference
ISSN
Citations 
PageRank 
2156-8103
1
0.35
References 
Authors
10
4
Name
Order
Citations
PageRank
Bo Xiao1828.31
Georgiou Panayiotis242855.79
Brian R. Baucom315216.36
Narayanan Shrikanth45558439.23