Projection defocus correction using adaptive kernel sampling and geometric correction in dual-planar environments

Defocus blur correction for projectors using a camera is useful when the projector is used in ad hoc environments. However, past literature has not explicitly considered the common situation when the projection surface includes a corner made up of two planar surfaces that abut each other, such as the ubiquitous office cubicle. In this paper, we advance the state of the art by demonstrating defocus correction in a non-parametric setting. Our method differs from prior methods in that (a) the luminance and chrominance channels are independently considered, and (b) a sparse sampling of the surface is used to discover the spatially varying defocus kernel.