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We present a method for precision intrinsic calibration of pinhole-model cameras. We refer to this method as "3-Axis." The algorithm employs a target moving with known displacements along three perpendicular axes to decrease the number of unknown terms that must be determined. This method along with new evaluation strategies for comparing the accuracy of pinhole camera calibration algorithms is described in detail. The 3-Axis approach is then compared with the current state-of-the art algorithms in simulated and physical settings and is shown to exceed them in accuracy and computational performance assuming an equal number of samples acquired. [ABSTRACT FROM AUTHOR]

Telecentric lenses have been used for high-precision visual measurement systems because of their unique imaging properties, whereas the principal point is usually not considered in the projection model for calibration. Here, we propose an improved model containing the principal point for calibrating telecentric cameras. Detailed mathematical derivation from the pinhole model is performed. Then, an experimental setup is established. Two different telecentric cameras are used for verification. The results prove that calibrating telecentric cameras based on the improved model considering the principal point can achieve up to 55.37% higher accuracy and better stability than the common projection model without the principal point. [ABSTRACT FROM AUTHOR]

Abstract. Laser triangulation and photometric stereo are commonly used three-dimensional (3-D) reconstruction methods, but they bear limitations in an underwater environment. One important reason is due to the refraction occurring at the interface (usually glass) of the underwater housing. The image formation process does not follow the commonly used pinhole camera model, and the image captured by the camera is a refracted projection of the object. We introduce a flat refraction model to describe the geometric relation between the refracted image and the real object. The model parameters were estimated in a calibration step with a standard chessboard. The proposed geometric relation is used for rebuilding underwater 3-D shapes in laser triangulation and photometric stereo. The experimental results indicate that our method can effectively correct the distortion in underwater 3-D reconstruction. [ABSTRACT FROM AUTHOR]

In real applications, a pinhole camera capturing objects through a planar parallel transparent plate is frequently employed. Due to the refractive effects of the plate, such an imaging system does not comply with the conventional pinhole camera model. Although the system is ubiquitous, it has not been thoroughly studied. This paper aims at presenting a simple virtual camera model, called a plate refractive camera model, which has a form similar to a pinhole camera model and can efficiently model refractions through a plate. The key idea is to employ a pixel-wise viewpoint concept to encode the refraction effects into a pixel-wise pinhole camera model. The proposed camera model realizes an efficient forward projection computation method and has some advantages in applications. First, the model can help to compute the caustic surface to represent the changes of the camera viewpoints. Second, the model has strengths in analyzing and rectifying the image caustic distortion caused by the plate refraction effects. Third, the model can be used to calibrate the camera's intrinsic parameters without removing the plate. Last but not least, the model contributes to putting forward the plate refractive triangulation methods in order to solve the plate refractive triangulation problem easily in multiviews. We verify our theory in both synthetic and real experiments. [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]

The fisheye-type camera is widely used since it has a larger view than that of a pinhole camera. But its applications have frequently been tortured by its higher distortion in imaging procedure. We propose a strategy for fisheye camera modeling based on the receptive field weighted regression algorithm. The camera's field of view is adaptively divided into multiple grids, each of which is described by an actively learned receptive field affiliated by a regression model to denote specific imaging relation in this grid with prescribed precision. The whole model of the camera is thus achieved by weighted regressions overall receptive fields on grids. Moreover, the proposed strategy could also be applied to the simultaneous calibration of a visual system of multiple cameras since the final sensing model stems from all receptive fields over any of the camera's field of view with the unified weighted regression scheme. Experiments on monocular and multicamera systems validate the feasibility of the proposed strategy, with performance comparisons with a state-of-the-art method. [ABSTRACT FROM AUTHOR]

We present a new algorithm for camera calibration using two concentric circles, which is a linear approach. In the calibration, a pinhole camera model is used. Different from previous methods, we take the projective equations of 3-D circles, which include the intrinsic parameter matrix of the camera, as the basis of our calibration approach. According to the special structure of the projective equations in algebra, we can get a linear equation system about the intrinsic parameters. After enough equations are constructed, the calibration can be easily finished. With at least three images of the two concentric circles, all five intrinsic parameters can be recovered. Experiments using computer simulated data and real data demonstrate the robustness and accuracy of our method. [ABSTRACT FROM AUTHOR]