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A structured light system with spinning fringe projection has been an excitement for three-dimensional (3-D) shape measurement since high-speed phase-shifting fringe patterns can be produced by mechanical spinning slide projectors. However, two cameras are typically required for 3-D reconstruction since the calibration method of spinning fringe projection is not well documented yet. This article introduces a computational framework for the calibration of spinning fringe projection profilometry using polar coordinate representation. In this preliminary study, we emulated the ideal spinning fringe projection with a video projector that can precisely control phase shifts with minimized harmonic errors. Results show that under the ideal scenario, our calibration method can reach an accuracy of 0.10 mm with a standard deviation of 0.73 mm by measuring a spherical object with 150 mm diameter. [ABSTRACT FROM AUTHOR]

With their large field of view, anamorphosis, and areas of enhanced magnification, panomorph lenses are an interesting choice for navigation systems for mobile robotics in which knowledge of the surroundings is mandatory. However, panomorph lenses special characteristics can be challenging during the calibration process. This study focuses on the calibration of two panomorph stereoscopic systems with a model and technique developed for narrow-angle lenses, the “Camera Calibration Toolbox for MATLAB.” In order to assess the performance of the systems, the mean reprojection error (MRE) related to the calibration and the reconstruction error of control points of an object of interest at various locations in the field of view are used. The calibrations were successful and exhibit MREs of less than one pixel in all cases. However, some poorly reconstructed control points illustrate that an acceptable MRE guarantees neither the quality of 3-D reconstruction nor its uniformity in the field of view. In addition, the nonuniformity in the 3-D reconstruction quality indicates that panomorph lenses require a more accurate estimation of the principal point (center of distortion) coordinates to improve the calibration and therefore the 3-D reconstruction. [ABSTRACT FROM AUTHOR]

An integral imaging (II) display is proposed which consists of a display panel and a gradient-aperture pinhole array. The gradient-aperture pinhole array is symmetrical in both horizontal and vertical directions. The leftmost and rightmost pinholes are used to fix the horizontal viewing angle, and the uppermost and nethermost pinholes are used to fix the vertical viewing angle. To increase the optical efficiency, the aperture widths of other pinholes are gradually increased from both sides to the middle in the horizontal and vertical directions, respectively. A prototype of the proposed II display is developed. Its horizontal viewing angle is equal to that of the conventional one, while its optical efficiency is higher than that of the conventional one. [ABSTRACT FROM AUTHOR]

For the existing monocular vision methods of pose (or position and orientation) measurement based on the Perspective-n-Point problem, camera calibrations and image corrections are complicated and difficult due to the lens distortion. Additionally, as their theoretical models, the pinhole imaging model and the collinear equation only offer an ideal approximation for the imaging process of the area array camera. Thus, the measurement possesses inevitable systematic errors. To avoid these problems, a new pose measuring method is proposed, which replaces the area array camera and its collinear equation with two line array cameras and their incident light plane equations, respectively. For these two line array cameras, their mechanical assembly requirements and calibration steps are also analysed; they only require that the two optical centre lines of their cylindrical lenses be perpendicular to each other, and only need to be calibrated for the relationship between the coordinate of the image line and the incident angle of the incident light plane. The experiment results of P4P pose measurement with the proposed method showed only significant random errors and no significant systematic error, confirming that this method has eliminated the problems caused by the image distortion and model approximation. [ABSTRACT FROM AUTHOR]