  Quantification of human attention is key to several tasks in mobile
human-computer interaction (HCI), such as predicting user interruptibility,
estimating noticeability of user interface content, or measuring user
engagement. Previous works to study mobile attentive behaviour required
special-purpose eye tracking equipment or constrained users' mobility. We
propose a novel method to sense and analyse visual attention on mobile devices
during everyday interactions. We demonstrate the capabilities of our method on
the sample task of eye contact detection that has recently attracted increasing
research interest in mobile HCI. Our method builds on a state-of-the-art method
for unsupervised eye contact detection and extends it to address challenges
specific to mobile interactive scenarios. Through evaluation on two current
datasets, we demonstrate significant performance improvements for eye contact
detection across mobile devices, users, or environmental conditions. Moreover,
we discuss how our method enables the calculation of additional attention
metrics that, for the first time, enable researchers from different domains to
study and quantify attention allocation during mobile interactions in the wild.
