Virtual and augmented realities are expected to become more and more important in everyday life in the next future; the role of spatial audio technologies over headphones will be pivotal for application scenarios which involve mobility. This paper introduces the SelfEar project, aimed at low-cost acquisition and personalization of Head-Related Transfer Functions (HRTFs) on mobile devices. This first version focuses on capturing individual spectral features which characterize external ear acoustics, through a self-adjustable procedure which guides users in collecting such information: their mobile device must be held with the stretched arm and positioned at several specific elevation points; acoustic data are acquired by an audio augmented reality headset which embeds a pair of microphones at listener ear-canals. A preliminary measurement session assesses the ability of the system to capture spectral features which are crucial for elevation perception. Moreover, a virtual experiment using a computational auditory model predicts clear vertical localization cues in the measured features.
