Music performances have transformed in unprecedented ways with the advent of digital music. Plenty of music visualizers enhance live performances in various forms, including LED display boards and holographic illustrations. However, the impracticability of live performances due to the CoVID-19 outbreak has led to event organizers adopting alternatives in virtual environments. In this work, we propose Liquid Hands, an Augmented Reality (AR) music visualizer system, wherein three-dimensional particles react to the flow of music, forming a visually aesthetic escapade. With hand-particle interactions, Liquid Hands aims to enrich the music listening experience in one’s personal space and bridge the gap between virtual and physical concerts. We intend to explore the emotions our system induces by conducting a pilot study, in which we measure the user’s psychological state through Electroencephalography (EEG). We hypothesize that the proposed system will evoke emotions akin to those exhibited in live music performances.

Entertainment is challenging to observe, especially with children, due to limited analytical tools. In response, we present a modified framework for entertainment computing, COMPASS -- COmbined Mental, PhysicAl, Social and Spatial factors, which we use to analyze augmented reality activities for cub scouts.

A common factor among current generation optical see-through augmented reality systems is fixed focal distance to virtual content. In this work, we investigate the issue of focus blur, in particular, the blurring caused by simultaneously viewing virtual content and physical objects in the environment at differing focal distances. We examine the application of dynamic sharpening filters as a straight forward, system independent, means for mitigating this effect improving the clarity of defocused AR content. We assess the utility of this method, termed SharpView, by employing an adjustment experiment in which users actively apply varying amounts of sharpening to reduce the perception of blur in AR content. Our experimental results validate the ability of our SharpView model to improve the visual clarity of focus blurred content, with optimal performance at focal differences well suited for near field AR applications.