Method for Prescribing Target Angles in Camera Testing

We propose a method of simultaneously calibrating the radial distortion function of a camera and the other internal calibration parameters. The method relies on the use of a planar (or, alternatively, nonplanar) calibration grid which is captured in several images. In this way, the determination of the radial distortion is an easy add-on to the popular calibration method proposed by Zhang [24]. The method is entirely noniterative and, hence, is extremely rapid and immune to the problem of local minima. Our method determines the radial distortion in a parameter-free way, not relying on any particular radial distortion model. This makes it applicable to a large range of cameras from narrow-angle to fish-eye lenses. The method also computes the center of radial distortion, which, we argue, is important in obtaining optimal results. Experiments show that this point may be significantly displaced from the center of the image or the principal point of the camera.

In this paper, we propose an image-based technique for panoramic novelview generation using three uncalibrated wide-angle images as its input. State of the art in novel view generation presumes the calibration and removal of radial distortion or any other deformation resulting from t he geometry of a non-central camera. We propose a method which replaces this calibration with the assumption that the epipole corresponding to the novel viewpoint is at the center of radial distortion and that it is known. 1 Introduction In novel view synthesis, given an image pair, the intensity of each ray in the novel view is determined by finding corresponding point matches betwee n those images, using the epipolar geometries between the two views and with respect to the novel view. This process requires that the given images obey the standard perspective model, with a single viewpoint and no radial distortion. Such assumptions make the creation of novel panoramas a process of acquiring tens of images, each with relatively narrow field-of-view, with special apparatus, and applying calibration and estimatio n of circular motion [9]. In this paper, we propose an approach where a novel view can be synthesized from multiple views which might be highly radially distorted, and even non-central, without compensating explicitly for the resulting image deformations. We shed new light on the problem (Fig. 1) of “how a scene looks from a scene point?”[8] by eliminating the need for a reference plane and facilitating synthesis of omnidre ctional novel views. We assume that, for n ≥ 3 views, the location of the epipole of the novel view in each image is known, and, in the case of radially distorted views, that it is coincident with the centre of radial distortion in the image. This assumption is either enforced (for example by choosing a visible scene point as the centre of projection of the view to be synthesized, and actually fixating on this point in the case of radially dis torted views), or else it may naturally be satisfied for certain wide-angle imaging syste ms (for example multiple views of a spherical mirror). Given such a configuration, the 2D sta r of virtual rays at the novel viewpoint are mapped to a 1D star of lines in each image, which we model as a projection from P 2 (the domain of the novel view) to P 1 (the angles of the line pencil in image plane). We make use of the well known fact that three projections of a line in space (a virtual line in our case) yield a trifocal constraint, from w hich we extract the projection matrices required for the view synthesis. The main contributions of this paper are:

We present a new robust method to determine the distortion function of camera systems suffering from radial lens distortion. It is based on single images and uses the distorted positions of collinear points. Neither information about the intrinsic camera parameters nor 3D-pointcorrespondences are required. The algorithm works without user interaction. The actual radial lens distortion of the most wide-angle and low-cost camera systems fits the used distortion model with two distortion coefficients sufficiently. The algorithm iteratively determines the distortion coefficients and the unknown co-ordinates of the principal point which is assumed to be identical with the symmetry point of the radial distortion. The results of experimental measurements of two different camera systems are presented and discussed.

The results of an earlier paper are extended to the special case of the electron microscope projector and similar type lenses It is shown that the focal properties of symmetrical projector lenses with different ratios of gap width S to lens bore D can be represented by a single curve. This is then applied to the discussion of various cases of practical interest. The calculated results are found to be in excellent agreement with measurements by Ruska The question of image distortion as a function of design parameters and lens excitation is then discussed; it is shown that all the types of lenses investigated can be operated at a point where they are free from `radial distortion'. A consideration of scaling operations shows that there is little difference between the optimum performance of lenses of different geometry, but equal focal length. Certain results of use in practical lens design are combined in a design chart from which the relevant design or operational parameters can be read directly. In conclusion, design rules are given for the optimum design of projector lenses covering a wide range of magnifications

The use of two-dimensional speckle tracking (2DST) for quantification of left ventricular (LV) function has recently been described in horses using long-axis images and short-axis images at chordal but not at papillary muscle level. To compare the feasibility and reliability of 2DST for quantification of circumferential and radial LV function in short-axis images at papillary muscle and chordal level. Repeated echocardiographic examinations were performed on 10 healthy trotter horses by 2 observers from a right parasternal short-axis view at papillary muscle and chordal level. Segmental and averaged peak values and timing of circumferential and radial strain and strain rate, radial displacement and rotation were measured in 6 LV wall segments in each imaging plane. Global peak values were calculated for circumferential strain and strain rate. The inter- and intraobserver within- and between-day variability was assessed by calculating coefficients of variation for repeated measurements. 2DST analysis was feasible in each cardiac cycle, although tracking was often inadequate during early diastole. Measurements of averaged systolic circumferential and radial strain and strain rate and radial displacement as well as global circumferential strain and strain rate could be determined with low variability. Early and late diastolic strain rate and systolic rotation showed a moderate variability. Radial segmental measurements were more reliable than circumferential measurements. The interventricular septum showed a higher circumferential and lower radial strain compared with the LV free wall. Peak timing was earlier at papillary muscle compared with chordal level. 2DST measurements of global and regional circumferential and radial LV wall motion are feasible both at papillary muscle and chordal level. Several measurements had good reliability and should be used for evaluation of the technique in a clinical setting.

The Lunar Reconnaissance Orbiter Camera (LROC) consists of two imaging systems that provide multispectral and high resolution imaging of the lunar surface. The Wide Angle Camera (WAC) is a seven color push-frame imager with a 90∘ field of view in monochrome mode and 60∘ field of view in color mode. From the nominal 50 km polar orbit, the WAC acquires images with a nadir ground sampling distance of 75 m for each of the five visible bands and 384 m for the two ultraviolet bands. The Narrow Angle Camera (NAC) consists of two identical cameras capable of acquiring images with a ground sampling distance of 0.5 m from an altitude of 50 km. The LROC team geometrically calibrated each camera before launch at Malin Space Science Systems in San Diego, California and the resulting measurements enabled the generation of a detailed camera model for all three cameras. The cameras were mounted and subsequently launched on the Lunar Reconnaissance Orbiter (LRO) on 18 June 2009. Using a subset of the over 793000 NAC and 207000 WAC images of illuminated terrain collected between 30 June 2009 and 15 December 2013, we improved the interior and exterior orientation parameters for each camera, including the addition of a wavelength dependent radial distortion model for the multispectral WAC. These geometric refinements, along with refined ephemeris, enable seamless projections of NAC image pairs with a geodetic accuracy better than 20 meters and sub-pixel precision and accuracy when orthorectifying WAC images.

Commercial Unmanned aerial vehicle (UAV) industry, which is publicly known as drone, has seen a tremendous increase in last few years, making these devices highly accessible to public. This phenomenon has immediately raised security concerns due to fact that these devices can intentionally or unintentionally cause serious hazards. In order to protect critical locations, the academia and industry have proposed several solutions in recent years. Computer vision is extensively used to detect drones autonomously compared to other proposed solutions such as RADAR, acoustics and RF signal analysis thanks to its robustness. Among these computer vision-based approaches, we see the preference of deep learning algorithms thanks to their effectiveness. In this paper, we are presenting an autonomous drone detection and tracking system which uses a static wide-angle camera and a lower-angle camera mounted on a rotating turret. In order to use memory and time efficiently, we propose a combined multi-frame deep learning detection technique, where the frame coming from the zoomed camera on the turret is overlaid on the wide-angle static camera’s frame. With this approach, we are able to build an efficient pipeline where the initial detection of small sized aerial intruders on the main image plane and their detection on the zoomed image plane is performed simultaneously, minimizing the cost of resource exhaustive detection algorithm. In addition to this, we present the integral system including tracking algorithms, deep learning classification architectures and the protocols.

A powerful and popular approach for estimating radial lens distortion parameters is to use the fact that lines which are straight in the scene should be imaged as straight lines under the pinhole camera model. This paper revisits this problem using the division model to parameterise the lens distortion. This turns out to have significant advantages over the more conventional parameterisation, especially for a single parameter model. In particular, we demonstrate that the locus of distorted points from a straight line is a circular arc. This allows distortion estimation to be reformulated as circle-fitting for which many algorithms are available. We compare a number of suboptimal methods offering closed-form solutions with an optimal, iterative technique which minimises a cost function on the actual image plane as opposed to existing techniques which suffer from a bias due to the fact that they optimise a geometric cost function on the undistorted image plane.

Regarding the distortion correction problem of large field of view wide-angle cameras commonly used in railway visual inspection systems, this paper proposes a novel online calibration method for non-specially made cooperative calibration objects. Based on the radial distortion divisor model, first, the spatial coordinates of natural spatial landmark points are constructed according to the known track gauge value between two parallel rails and the spacing value between sleepers. By using the image coordinate relationships corresponding to these spatial coordinates, the coordinates of the distortion center point are solved according to the radial distortion fundamental matrix. Then, a constraint equation is constructed based on the collinear constraint of vanishing points in railway images, and the Levenberg–Marquardt algorithm is used to found the radial distortion coefficients. Moreover, the distortion coefficients and the coordinates of the distortion center are re-optimized according to the least squares method (LSM) between points and the fitted straight line. Finally, based on the above, the distortion correction is carried out for the distorted railway images captured by the camera. The experimental results show that the above method can efficiently and accurately perform online distortion correction for large field of view wide-angle cameras used in railway inspection without the participation of specially made cooperative calibration objects. The whole method is simple and easy to implement, with high correction accuracy, and is suitable for the rapid distortion correction of camera images in railway online visual inspection.

The images captured by real cameras often suffer from lens distortion which is a nonlinear and radial distortion. In this work, we present a method to correct the radial distortion caused by camera lens. In particular, we discuss a framework to determine distortion vectors and distortion function directly without employing approximation approach which often causes incorrect warping problem. The proposed framework is entirely non-iterative, and therefore is computationally efficient. We also compute the center of distortion, which is important to obtain optimal results. The accuracy and robustness of the proposed system are verified on the experimental results of several indoor and outdoor images.

Hough transform for feature detection in panoramic images

Lunar lander's three-dimensional translation and yaw rotation motion estimation during a descent phase using optical navigation

Multislice Approach to Lens Analysis

Geometrical optics analysis for reduction of trapezoidal image distortion in a single prism-based optical fingerprint scanner

In this study, we present a new calibration method for the cooperation of wide-angle and pan-tilt-zoom (PTZ) cameras. A wide-angle camera enables the surveillance of a large area. However, it may be difficult to perceive the detail of an object. On the other hand, a PTZ camera enables the surveillance of the object detail. However, its view is limited when the camera zooms on a specific object. Therefore, the cooperation can complement the disadvantage of two types of cameras. For an object appears in the image of wide-angle camera, the desired pan and tilt angles of a PTZ camera for focusing on the object can be computed from its image coordinate. Previous methods can be classified into three categories: 3D world coordinate system, scene-dependent, or special technique. They are not simple and instinctive enough. The proposed method is simply based on the 2D image plane of wide-angle camera. A set of calibration points are selected directly on the image. Every point is a pair of pan/tilt angles (p, t) and 2D coordinate (x, y). Then, the calibration parameters are calculated from the set of points. An experiment was designed to evaluate the accuracy of the proposed method at fixed points. The results show that the proposed method is accurate enough for the cooperation of dual cameras. In advance, a prototype system for capturing close-up images of moving objects in an open area was implemented to demonstrate the feasibility of the proposed method.