A major limitation of existing projection display systems is that they rely on a high quality screen for projecting images. We believe that relaxing this restriction will make projectors more useful and widely applicable. The fundamental problem with using an arbitrary surface for a screen is that the surface is bound to have its own colors and textures (bricks of a wall, painting on a wall, tiles of a ceiling, grain of a wooden door, etc.) or surface markings (paint imperfections, scratches, nails, etc.). As a result, when an image is projected onto the surface, the appearance of the image is modulated by the spatially varying reflectance properties of the surface. Humans are very sensitive to such modulations.

In this project, we are developing methods that enables a projector to display images onto an arbitrary surface such that the quality of the images is preserved and the effects of the surface imperfections are minimized. All of our methods are based on efficient algorithms for radiometric calibration that determine the mapping of projector colors to camera colors onto the unknown projection surface. The camera is used here as a proxy for the human observer. The computed calibration parameters are then used online to compensate each display image prior to projection. We have determined the minimum number of images needed to perform such a radiometric calibration. We have also extended our compensation method to handle arbitrary 3D objects. Finally, we have developed an adaptive compensation algorithm that can update (in real-time) previously computed radiometric calibration parameters and project images with compensation on dynamic (time-varying) scenes. Our results have applications in several areas including smart environments, product design and presentation, adaptive camouflages, interactive education and entertainment.