7,655 research outputs found

    Normal frames for non-Riemannian connections

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    The principal properties of geodesic normal coordinates are the vanishing of the connection components and first derivatives of the metric components at some point. It is well-known that these hold only at points where the connection has vanishing torsion and non-metricity. However, it is shown that normal frames, possessing the essential features of normal coordinates, can still be constructed when the connection is non-Riemannian.Comment: 4 pages, plain TeX. To appear in Class. Quantum Gra

    Support Vector Machine classification of strong gravitational lenses

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    The imminent advent of very large-scale optical sky surveys, such as Euclid and LSST, makes it important to find efficient ways of discovering rare objects such as strong gravitational lens systems, where a background object is multiply gravitationally imaged by a foreground mass. As well as finding the lens systems, it is important to reject false positives due to intrinsic structure in galaxies, and much work is in progress with machine learning algorithms such as neural networks in order to achieve both these aims. We present and discuss a Support Vector Machine (SVM) algorithm which makes use of a Gabor filterbank in order to provide learning criteria for separation of lenses and non-lenses, and demonstrate using blind challenges that under certain circumstances it is a particularly efficient algorithm for rejecting false positives. We compare the SVM engine with a large-scale human examination of 100000 simulated lenses in a challenge dataset, and also apply the SVM method to survey images from the Kilo-Degree Survey.Comment: Accepted by MNRA

    Autocalibration with the Minimum Number of Cameras with Known Pixel Shape

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    In 3D reconstruction, the recovery of the calibration parameters of the cameras is paramount since it provides metric information about the observed scene, e.g., measures of angles and ratios of distances. Autocalibration enables the estimation of the camera parameters without using a calibration device, but by enforcing simple constraints on the camera parameters. In the absence of information about the internal camera parameters such as the focal length and the principal point, the knowledge of the camera pixel shape is usually the only available constraint. Given a projective reconstruction of a rigid scene, we address the problem of the autocalibration of a minimal set of cameras with known pixel shape and otherwise arbitrarily varying intrinsic and extrinsic parameters. We propose an algorithm that only requires 5 cameras (the theoretical minimum), thus halving the number of cameras required by previous algorithms based on the same constraint. To this purpose, we introduce as our basic geometric tool the six-line conic variety (SLCV), consisting in the set of planes intersecting six given lines of 3D space in points of a conic. We show that the set of solutions of the Euclidean upgrading problem for three cameras with known pixel shape can be parameterized in a computationally efficient way. This parameterization is then used to solve autocalibration from five or more cameras, reducing the three-dimensional search space to a two-dimensional one. We provide experiments with real images showing the good performance of the technique.Comment: 19 pages, 14 figures, 7 tables, J. Math. Imaging Vi

    Transients in sheared granular matter

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    As dense granular materials are sheared, a shear band and an anisotropic force network form. The approach to steady state behavior depends on the history of the packing and the existing force and contact network. We present experiments on shearing of dense granular matter in a 2D Couette geometry in which we probe the history and evolution of shear bands by measuring particle trajectories and stresses during transients. We find that when shearing is stopped and restarted in the same direction, steady state behavior is immediately reached, in agreement with the typical assumption that the system is quasistatic. Although some relaxation of the force network is observed when shearing is stopped, quasistatic behavior is maintained because the contact network remains essentially unchanged. When the direction of shear is reversed, a transient occurs in which stresses initially decrease, changes in the force network reach further into the bulk, and particles far from the wheel become more mobile. This occurs because the force network is fragile to changes transverse to the force network established under previous shear; particles must rearrange before becoming jammed again, thereby providing resistance to shear in the reversed direction. The strong force network is reestablished after displacing the shearing surface ≈3d\approx 3d, where dd is the mean grain diameter. Steady state velocity profiles are reached after a shear of ≀30d\leq 30d. Particles immediately outside of the shear band move on average less than 1 diameter before becoming jammed again. We also examine particle rotation during this transient and find that mean particle spin decreases during the transient, which is related to the fact that grains are not interlocked as strongly.Comment: 7 pages, 11 figures, accepted to Eur. Phys. J. E, revised version based on referee suggestion

    Self-Calibration of Cameras with Euclidean Image Plane in Case of Two Views and Known Relative Rotation Angle

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    The internal calibration of a pinhole camera is given by five parameters that are combined into an upper-triangular 3×33\times 3 calibration matrix. If the skew parameter is zero and the aspect ratio is equal to one, then the camera is said to have Euclidean image plane. In this paper, we propose a non-iterative self-calibration algorithm for a camera with Euclidean image plane in case the remaining three internal parameters --- the focal length and the principal point coordinates --- are fixed but unknown. The algorithm requires a set of N≄7N \geq 7 point correspondences in two views and also the measured relative rotation angle between the views. We show that the problem generically has six solutions (including complex ones). The algorithm has been implemented and tested both on synthetic data and on publicly available real dataset. The experiments demonstrate that the method is correct, numerically stable and robust.Comment: 13 pages, 7 eps-figure

    Program for transfer research and impact studies

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    Research activities conducted under the Program for Transfer Research and Impact Studies (TRIS) during 1972 included: (1) preparation of 10,196 TSP requests for TRIS application analysis; (2) interviews with over 500 individuals concerning the technical, economic, and social impacts of NASA-generated technology; (3) preparation of 38 new technology transfer example files and 101 new transfer cases; and (4) maintenance of a technology transfer library containing more than 2,900 titles. Six different modes of technology utilization are used to illustrate the pervasiveness of the transfer and diffusion of aerospace innovations. These modes also provide a basis for distinguishing the unique characteristics of the NASA Technology Utilization Program. An examination is reported of the ways in which NASA-generated technology is contributing to beneficial social change in five major areas of human concern: health, environment, safety, transportation, and communication

    Collaboration and teamwork: immersion and presence in an online learning environment

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    In the world of OTIS, an online Internet School for occupational therapists, students from four European countries were encouraged to work collaboratively through problem-based learning by interacting with each other in a virtual semi-immersive environment. This paper describes, often in their own words, the experience of European occupational therapy students working together across national and cultural boundaries. Collaboration and teamwork were facilitated exclusively through an online environment, since the students never met each other physically during the OTIS pilot course. The aim of the paper is to explore the observations that here was little interaction between students from different tutorial groups and virtual teamwork developed in each of the cross-cultural tutorial groups. Synchronous data from the students was captured during tutorial sessions and peer-booked meetings and analysed using the qualitative constructs of ‘immersion’, ‘presence’ and ‘reflection in learning’. The findings indicate that ‘immersion’ was experienced only to a certain extent. However, both ‘presence’ and shared presence were found by the students, within their tutorial groups, to help collaboration and teamwork. Other evidence suggests that communities of interest were established. Further study is proposed to support group work in an online learning environment. It is possible to conclude that collaborative systems can be designed, which encourage students to build trust and teamwork in a cross cultural online learning environment.</p

    A PCA-based automated finder for galaxy-scale strong lenses

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    We present an algorithm using Principal Component Analysis (PCA) to subtract galaxies from imaging data, and also two algorithms to find strong, galaxy-scale gravitational lenses in the resulting residual image. The combined method is optimized to find full or partial Einstein rings. Starting from a pre-selection of potential massive galaxies, we first perform a PCA to build a set of basis vectors. The galaxy images are reconstructed using the PCA basis and subtracted from the data. We then filter the residual image with two different methods. The first uses a curvelet (curved wavelets) filter of the residual images to enhance any curved/ring feature. The resulting image is transformed in polar coordinates, centered on the lens galaxy center. In these coordinates, a ring is turned into a line, allowing us to detect very faint rings by taking advantage of the integrated signal-to-noise in the ring (a line in polar coordinates). The second way of analysing the PCA-subtracted images identifies structures in the residual images and assesses whether they are lensed images according to their orientation, multiplicity and elongation. We apply the two methods to a sample of simulated Einstein rings, as they would be observed with the ESA Euclid satellite in the VIS band. The polar coordinates transform allows us to reach a completeness of 90% and a purity of 86%, as soon as the signal-to-noise integrated in the ring is higher than 30, and almost independent of the size of the Einstein ring. Finally, we show with real data that our PCA-based galaxy subtraction scheme performs better than traditional subtraction based on model fitting to the data. Our algorithm can be developed and improved further using machine learning and dictionary learning methods, which would extend the capabilities of the method to more complex and diverse galaxy shapes
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