Robust visual odometry using uncertainty models

In dense, urban environments, GPS by itself cannot be relied on to provide accurate positioning information. Signal reception issues (e.g. occlusion, multi-path effects) often prevent the GPS receiver from getting a positional lock, causing holes in the absolute positioning data. In order to keep assisting the driver, other sensors are required to track the vehicle motion during these periods of GPS disturbance. In this paper, we propose a novel method to use a single on-board consumer-grade camera to estimate the relative vehicle motion. The method is based on the tracking of ground plane features, taking into account the uncertainty on their backprojection as well as the uncertainty on the vehicle motion. A Hough-like parameter space vote is employed to extract motion parameters from the uncertainty models. The method is easy to calibrate and designed to be robust to outliers and bad feature quality. Preliminary testing shows good accuracy and reliability, with a positional estimate within 2 metres for a 400 metre elapsed distance. The effects of inaccurate calibration are examined using artificial datasets, suggesting a self-calibrating system may be possible in future work

Why Do Granular Materials Stiffen with Shear Rate? : Test of Novel Stress-Based Statistics

Peer reviewedPublisher PD

Assessing the effect of friction on compression split Hopkinson pressure bar tests

An enhanced understanding of material behaviour during rapid loading allows designers to improve the safety and efficiency of industrial processes and commercial products. These improvements are due, in part, to the use of increasingly powerful and sophisticated numerical simulation codes, which in tum, depend on accurate high strain rate material data. A Split Hopkinson Pressure Bar (SHPB) facility had previously been developed at the University of Cape Town to allow high strain rate testing of materials in compression. However, uncertainties regarding aspects of the test method that can affect the accuracy of the results, such as interface friction and specimen inertia, still required further clarification. This report details a thorough experimental and numerical investigation into the effect of friction on SHPB test data. The objectives are to assess the magnitude of the effect of friction under various conditions and to suggest strategies for reducing friction error in SHPB tests to an acceptable level. The ring compression test was used to obtain experimental friction factors. The effect of surface finish, lubricant, and strain rate on the friction experienced by mild steel, copper and aluminium samples was investigated. Numerical simulation was used to assess an energy-based analytical solution by Avitzur [1], and in particular to establish the effect of neglecting barrelling. Avitzur's analytical solution [l] Was then used to interpret the experimental results. The tested specimen microstructure was examined and used to estimate the stress distribution in the specimen during deformation. Uneven deformation and fold-over diminished at higher strain rates. Optimal surface finish and lubricant conditions were found for which experimentally measured coulomb friction coefficients lay between J.l = 0.04 and 0.08, with copper samples exhibiting marginally higher friction. By Avitzur's analytical solution [1] the error in SHPB tests under these recommended conditions was estimated to lie between 1% and 2%. The results show that roughened compression and specimen surfaces, lubricated with a suitable grease containing molybdenum disulphide, are useful in effectively reducing the error in SHPB tests due to friction effects

Support Vector Machine classification of strong gravitational lenses

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

NGO perspectives on the social and ethical dimensions of plant genome-editing

Plant genome editing has the potential to become another chapter in the intractable debate that has dogged agricultural biotechnology. In 2016, 107 Nobel Laureates accused Greenpeace of emotional and dogmatic campaigning against agricultural biotechnology and called for governments to defy such campaigning. The Laureates invoke the authority of science to argue that Greenpeace is putting lives at risk by opposing agricultural biotechnology and Golden Rice and is notable in framing Greenpeace as unethical and its views as marginal. This paper examines environmental, food and farming NGOs’ social and ethical concerns about genome editing, situating these concerns in comparison to alternative ethical assessments provided by the Nuffield Council on Bioethics, a key actor in this policy debate. In doing so, we show that participant NGOs and the Nuffield Council on Bioethics share considerable concerns about the social and ethical implications of genome editing. These concerns include choices over problem/solution framing and broader terminology, implications of regulatory and research choices on consumer choice and relations of power. However, GM-engaged NGOs and the Nuffield Council on Bioethics diverge on one important area: the NGOs seek to challenge the existing order and broaden the scope of debate to include deeply political questions regarding agricultural and technological choices. This distinction between the ethical positions means that NGOs provide valuable ethical insight and a useful lens to open up debate and discussion on the role of emerging technologies, such as genome editing, and the future of agriculture and food sovereignty

Hybrid Focal Stereo Networks for Pattern Analysis in Homogeneous Scenes

In this paper we address the problem of multiple camera calibration in the presence of a homogeneous scene, and without the possibility of employing calibration object based methods. The proposed solution exploits salient features present in a larger field of view, but instead of employing active vision we replace the cameras with stereo rigs featuring a long focal analysis camera, as well as a short focal registration camera. Thus, we are able to propose an accurate solution which does not require intrinsic variation models as in the case of zooming cameras. Moreover, the availability of the two views simultaneously in each rig allows for pose re-estimation between rigs as often as necessary. The algorithm has been successfully validated in an indoor setting, as well as on a difficult scene featuring a highly dense pilgrim crowd in Makkah.Comment: 13 pages, 6 figures, submitted to Machine Vision and Application

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

The internal calibration of a pinhole camera is given by five parameters that are combined into an upper-triangular $3\times 3$ 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 $N \geq 7$ 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

Autocalibration with the Minimum Number of Cameras with Known Pixel Shape

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

On Parametrically Excited Flexural Motion of an Extensible and Shearable Rod with a Heavy Attachment

A simple Cosserat model is used to explore the coupled planar flemural and arial vibrations of a slender rod clamped at one end with a heauy attached mass free to move at the other. By assuming that the inertia of the rod is small compared to that of the attached mass it is shown how the equations of motionreduce to a dynamical system. The effects of grauity on the rod can be incorporated within this frame-work and the linearised stability of the system discussed in terms of solutions to the Mathieu-Hill equation

Exploring the use of strategic frameworks in dental practice

This paper explores the use of strategic frameworks in NHS and private dental practice. It reviews the policy context of dentistry and suggests the challenges in this context will require dental practices to prioritise understanding and engagement with a strategic approach. A strategic approach will be required in order to enhance and improve performance. Two specific strategic frameworks will be explored in terms of their relevance to NHS and private dental practic