Computational modeling of head-eye coordination in face-to-face behavior

In this paper, we propose a computational modeling method to investigate head-eye coordination in face-to-face behavior. The method looks into probability density of individuals' head orientation during looking at others' face. We conducted experiment under two different scenarios in human-human interaction. Under each scenario, individuals' head orientation could be fitted with one Gaussian distribution. Referring to the model, it is possible to calculate several ranges of head orientation, which could be used as surrogate for estimating visual focus of attention. The model also provides theoretical support to the design of automatic systems that measure face-to-face interaction.

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