Projection Mapping (PM) is a technology that projects images onto the surfaces of physical objects, allowing multiple users to share an augmented reality experience without special devices. However, its practical use has been constrained by the need for dark environments to ensure high-quality projection. To overcome this "dark-room constraint," we propose a novel target-excluding lighting method that selectively illuminates the surrounding environment while avoiding the PM target. Our system achieves light-field illumination by combining an LED display panel with an optimized aperiodic lens array. The key contributions include a compact form factor that provides a large effective light source area, reproducing natural soft shadows comparable to typical lighting, while maintaining the spatial controllability needed to precisely avoid the target. We also introduce a computational technique for optimizing aperiodic lens placement to suppress undesired dark spots caused by crosstalk, and efficient methods for computing LED luminance patterns that enable dynamic PM. Experiments with a prototype system demonstrate that our approach achieves high-contrast PM even in bright environments.

This paper proposes a projection system that optically removes the cast shadow in projection mapping. Specifically, we realize the large-aperture (LA) projection using a large-format Fresnel lens to suppress cast shadows by condensing the projection light from a wide viewing angle. However, the resolution and contrast of the projected results are significantly degraded by defocus blur, veiling glare, and stray light caused by the aberration of an LA Fresnel lens. To solve the technical problems, we employ two different approaches: optical and digital image processing methods. First, we introduce a residual projector with a typical aperture lens on the same optical axis as the LA projector, projecting the residual (i.e., high-frequency) components attenuated in the LA projection. These projectors play different roles in shadow suppression and blur compensation, both achieved by projecting simultaneously. Secondly, we optimize the pair of projection images that can balance the shadow suppression and deblurring performance of our projection system. We implemented a proof-of-concept prototype and validated the above-mentioned techniques through projection experiments and a user study.

Projection mapping (PM) is a technique that enhances the appearance of real-world surfaces using projected images, enabling multiple people to view augmentations simultaneously, thereby facilitating communication and collaboration. However, PM typically requires a dark environment to achieve high-quality projections, limiting its practicality. In this paper, we overcome this limitation by replacing conventional room lighting with heterogeneous projectors. These projectors replicate environmental lighting by selectively illuminating the scene, excluding the projection target. Our contributions include a distributed projector optimization framework designed to effectively replicate environmental lighting and the incorporation of a large-aperture projector, in addition to standard projectors, to reduce high-luminance emitted rays and hard shadows-undesirable factors for collaborative tasks in PM. We conducted a series of quantitative and qualitative experiments, including user studies, to validate our approach. Our findings demonstrate t hat our projector-based lighting system significantly enhancesthe contrast and realism of PM results even under e nvironmental lighting compared to typical lights. Furthermore, our method facilitates a substantial shift in the perceived color mode from the undesirable aperture-color mode, where observers perceive the projected object as self-luminous, to the surface-color mode in PM.