This paper introduces a novel photometric compensation technique for inter-projector luminance and chrominance variations. Although it sounds as a classical technical issue, to the best of our knowledge there is no existing solution to alleviate the spatial non-uniformity among strongly heterogeneous projectors at perceptually acceptable quality. Primary goal of our method is increasing the perceived seamlessness of the projection system by automatically generating an improved and consistent visual quality. It builds upon the existing research of multi-projection systems, but instead of working with perceptually non-uniform color spaces such as CIEXYZ, the overall computation is carried out using the RLab [10, pp. 243-254] color appearance model which models the color processing in an adaptive, perceptual manner. Besides, we propose an adaptive color gamut acquisition, spatially varying gamut mapping, and optimization framework for edge blending. The paper describes the overall workflow and detailed algorithm of each component, followed by an evaluation validating the proposed method. The experimental results both qualitatively and quantitatively show the proposed method significant improved the visual quality of projected results of a multi-projection display with projectors with severely heterogeneous color processing.

Calibration of multi-projector-camera systems (MPCS) is a cumbersome and time-consuming process. It is of great importance to have robust, fast and accurate calibration procedures at hand for a wide variety of practical applications. We propose a fully automated self-calibration method for arbitrarily complex MPCS. It enables reliable and accurate intrinsic and extrinsic calibration without any human parameter tuning. We evaluated the proposed methods using more than ten multi-projection datasets ranging from a toy castle set up consisting of three cameras and one projector up to a half dome display system with more than 30 devices. Comparisons to reference calibrations, which were generated using the standard checkerboard calibration approach [44], show the reliability of our proposed pipeline, while a ground truth evaluation also shows that the resulting reconstructed point cloud accurately matches the shape of the reference geometry. Besides being fully automatic without the necessity of parameter fine tuning, the proposed method also significantly reduces the installation time of MPCS compared to checkerboard-based methods and makes it more suitable for real-world applications.

We present a geometric calibration method to accurately register a galvanoscopic scanning laser projection system (GLP) based on 2D vector input data onto an arbitrarily complex 3D-shaped projection surface. This method allows for accurate merging of 3D vertex data displayed on the laser projector with geometrically calibrated standard rasterization-based video projectors that are registered to the same geometry. Because laser projectors send out a laser light beam via galvanoscopic mirrors, a standard pinhole model calibration procedure that is normally used for pixel raster displays projecting structured light patterns, such as Gray codes, cannot be carried out directly with sufficient accuracy as the rays do not converge into a single point. To overcome the complications of accurately registering the GLP while still enabling a treatment equivalent to a standard pinhole device, an adapted version is applied to enable straightforward content generation. Besides the geometrical calibration, we also present a photometric calibration to unify the color appearance of GLPs and standard video projectors maximizing the advantages of the large color gamut of the GLP and optimizing its color appearance to smoothly fade into the significantly smaller gamut of the video projector. The proposed algorithms were evaluated on a prototypical mixed video projector and GLP projection mapping setup.

Galvanoscopic scanning laser projectors are powerful vector graphic devices offering a tremendous local brightness advantage compared to standard video projection systems. However, such devices have inherent problems, such as temporal flicker and spatially inaccurate rendering. We propose a method to generate an accurate point-based projection with such devices. To overcome the mentioned problems, we present a camera-based method to automatically analyze the laser projector's motion behavior. With this information, a model database is generated that is used to optimize the scanning path of projected point sequences. The optimization considers the overall path length, its angular shape, acceleration behavior, and the spatio-temporal point neighborhood. The method minimizes perceived visual flickering while guaranteeing an accurate spatial point projection at the same time. Comparisons and timing measurements prove the effectiveness of our method. An informal user evaluation shows substantial visual quality improvement as well.