Direct Image Alignment of Projector-Camera Systems with Planar Surfaces

Abstract

Projector-camera systems use computer vision to analyze their surroundings and display feedback directly onto real world objects, as embodied by spatial augmented reality. To be effective, the display must remain aligned even when the target object moves, but the added illumination causes problems for traditional algorithms. Current solutions consider the displayed content as interference and largely depend on channels orthogonal to visible light. They cannot directly align projector images with real world surfaces, even though this may be the actual goal. We propose instead to model the light emitted by projectors and reflected into cameras, and to consider the displayed content as additional information useful for direct alignment. We implemented in software an algorithm that successfully executes on planar surfaces of diffuse reflectance properties at almost two frames per second with subpixel accuracy. Although slow, our work proves the viability of the concept, paving the way for future optimization and generalization.