Today's Virtual Reality (VR) displays are dramatically better than the head-worn displays offered 30 years ago, but today's displays remain nearly as bulky as their predecessors in the 1980's. Also, almost all consumer VR displays today provide 90-110 degrees field of view (FOV), which is much smaller than the human visual system's FOV which extends beyond 180 degrees horizontally. In this paper, we propose ThinVR as a new approach to simultaneously address the bulk and limited FOV of head-worn VR displays. ThinVR enables a head-worn VR display to provide 180 degrees horizontal FOV in a thin, compact form factor. Our approach is to replace traditional large optics with a curved microlens array of custom-designed heterogeneous lenslets and place these in front of a curved display. We found that heterogeneous optics were crucial to make this approach work, since over a wide FOV, many lenslets are viewed off the central axis. We developed a custom optimizer for designing custom heterogeneous lenslets to ensure a sufficient eyebox while reducing distortions. The contribution includes an analysis of the design space for curved microlens arrays, implementation of physical prototypes, and an assessment of the image quality, eyebox, FOV, reduction in volume and pupil swim distortion. To our knowledge, this is the first work to demonstrate and analyze the potential for curved, heterogeneous microlens arrays to enable compact, wide FOV head-worn VR displays.

This paper explores whether it is effective to use real-time on-screen guidance to help users take better photos with mobile devices. Using a three-camera array, we developed a photo-taking interface that provides real-time feedback on how to position the subject-of-interest according to a photography composition rule: rule-of-thirds. We conduct a user study to compare the aesthetic quality of photos taken with our real-time guidance interface against a static gridline interface common to existing digital cameras. Expert photographers and Mechanical Turk workers rate the aesthetic quality of these pairs of photos. Results indicate the photos taken with our real-time guidance interface have significantly higher aesthetics scores. This study shows the potential in using camera array, computational photography, and real-time guidance interface to help non-expert users take better photos.