Standard approaches to computing interpolated (in-between) frames in a video sequence require accurate pixel correspondences between images e.g. using optical flow. We present an efficient alternative by leveraging recent developments in phase-based methods that represent motion in the phase shift of individual pixels. This concept allows in-between images to be generated by simple per-pixel phase modification, without the need for any form of explicit correspondence estimation. Up until now, such methods have been limited in the range of motion that can be interpolated, which fundamentally restricts their usefulness. In order to reduce these limitations, we introduce a novel, bounded phase shift correction method that combines phase information across the levels of a multi-scale pyramid. Additionally, we propose extensions for phase-based image synthesis that yield smoother transitions between the interpolated images. Our approach avoids expensive global optimization typical of optical flow methods, and is both simple to implement and easy to parallelize. This allows us to interpolate frames at a fraction of the computational cost of traditional optical flow-based solutions, while achieving similar quality and in some cases even superior results. Our method fails gracefully in difficult interpolation settings, e.g., significant appearance changes, where flow-based methods often introduce serious visual artifacts. Due to its efficiency, our method is especially well suited for frame interpolation and retiming of high resolution, high frame rate video.

Coding a projector's aperture plane with adaptive patterns together with inverse filtering allow the depth-of-field of projected imagery to be increased. We present two prototypes and corresponding algorithms for static and programmable apertures. We also explain how these patterns can be computed at interactive rates, by taking into account the image content and limitations of the human visual system. Applications such as projector defocus compensation, high-quality projector depixelation, and increased temporal contrast of projected video sequences can be supported. Coded apertures are a step towards next-generation auto-iris projector lenses.

We present a system that employs a custom-built pan-tilt-zoom camera for laser pointer tracking in arbitrary real environments. Once placed in a room, it carries out a fully automatic self-registration, registrations of projectors, and sampling of surface parameters, such as geometry and reflectivity. After these steps, it can be used for tracking a laser spot on the surface as well as an LED marker in 3D space, using inter-playing fish-eye context and controllable detail cameras. The captured surface information can be used for masking out areas that are problematic for laser pointer tracking, and for guiding geometric and radiometric image correction techniques that enable a projector-based augmentation on arbitrary surfaces. We describe a distributed software framework that couples laser pointer tracking for interaction, projector-based AR as well as video see-through AR for visualizations, with the domain specific functionality of existing desktop tools for architectural planning, simulation and building surveying.