Thesis (Ph. D.)--University of Wisconsin--Madison, 1987. / Typescript. Vita. Description based on print version record. Includes bibliographical references (leaves 148-157).

Thesis (M.S.)--University of Wisconsin--Madison, 1966. / eContent provider-neutral record in process. Description based on print version record. Bibliography: l. 56.

Thesis (M. Sc.)--Syracuse University, 1939. / Bibliography: p. 43.

This thesis investigates new convex optimisation techniques for motion and pose estimation. Numerous computer vision problems can be formulated as optimisation problems. These optimisation problems are generally solved via linear techniques using the singular value decomposition or iterative methods under an L2 norm minimisation. Linear techniques have the advantage of offering a closed-form solution that is simple to implement. The quantity being minimised is, however, not geometrically or statistically meaningful. Conversely, L2 algorithms rely on iterative estimation, where a cost function is minimised using algorithms such as Levenberg-Marquardt, Gauss-Newton, gradient descent or conjugate gradient. The cost functions involved are geometrically interpretable and can statistically be optimal under an assumption of Gaussian noise. However, in addition to their sensitivity to initial conditions, these algorithms are often slow and bear a high probability of getting trapped in a local minimum or producing infeasible solutions, even for small noise levels. In light of the above, in this thesis we focus on developing new techniques for finding solutions via a convex optimisation framework that are globally optimal. Presently convex optimisation techniques in motion estimation have revealed enormous advantages. Indeed, convex optimisation ensures getting a global minimum, and the cost function is geometrically meaningful. Moreover, robust optimisation is a recent approach for optimisation under uncertain data. In recent years the need to cope with uncertain data has become especially acute, particularly where real-world applications are concerned. In such circumstances, robust optimisation aims to recover an optimal solution whose feasibility must be guaranteed for any realisation of the uncertain data. Although many researchers avoid uncertainty due to the added complexity in constructing a robust optimisation model and to lack of knowledge as to the nature of these uncertainties, and especially their propagation, in this thesis robust convex optimisation, while estimating the uncertainties at every step is investigated for the motion estimation problem. First, a solution using convex optimisation coupled to the recursive least squares (RLS) algorithm and the robust H filter is developed for motion estimation. In another solution, uncertainties and their propagation are incorporated in a robust L convex optimisation framework for monocular visual motion estimation. In this solution, robust least squares is combined with a second order cone program (SOCP). A technique to improve the accuracy and the robustness of the fundamental matrix is also investigated in this thesis. This technique uses the covariance intersection approach to fuse feature location uncertainties, which leads to more consistent motion estimates. Loop-closure detection is crucial in improving the robustness of navigation algorithms. In practice, after long navigation in an unknown environment, detecting that a vehicle is in a location it has previously visited gives the opportunity to increase the accuracy and consistency of the estimate. In this context, we have developed an efficient appearance-based method for visual loop-closure detection based on the combination of a Gaussian mixture model with the KD-tree data structure. Deploying this technique for loop-closure detection, a robust L convex posegraph optimisation solution for unmanned aerial vehicle (UAVs) monocular motion estimation is introduced as well. In the literature, most proposed solutions formulate the pose-graph optimisation as a least-squares problem by minimising a cost function using iterative methods. In this work, robust convex optimisation under the L norm is adopted, which efficiently corrects the UAV’s pose after loop-closure detection. To round out the work in this thesis, a system for cooperative monocular visual motion estimation with multiple aerial vehicles is proposed. The cooperative motion estimation employs state-of-the-art approaches for optimisation, individual motion estimation and registration. Three-view geometry algorithms in a convex optimisation framework are deployed on board the monocular vision system for each vehicle. In addition, vehicle-to-vehicle relative pose estimation is performed with a novel robust registration solution in a global optimisation framework. In parallel, and as a complementary solution for the relative pose, a robust non-linear H solution is designed as well to fuse measurements from the UAVs’ on-board inertial sensors with the visual estimates. The suggested contributions have been exhaustively evaluated over a number of real-image data experiments in the laboratory using monocular vision systems and range imaging devices. In this thesis, we propose several solutions towards the goal of robust visual motion estimation using convex optimisation. We show that the convex optimisation framework may be extended to include uncertainty information, to achieve robust and optimal solutions. We observed that convex optimisation is a practical and very appealing alternative to linear techniques and iterative methods.

Two introductory chapters have been used to give the necessary background to the main subject-matter of the thesis. The first of these chronologizes the significant steps in the development of aerial photographic interpretation from the first recorded aerial photograph to the present day respected position of the art in both military and civilian professional circles. The second introductory chapter deals with the fundamental principles involved in airphoto interpretation and of their specific application to soil engineering mapping for road projects in Southern Africa. This is followed by the major theme of the thesis, which concerns the direct location by aerial photographic interpretation of the various classes of material used in the construction of a modern day road. Although aerial photographs have been employed in recent years for direct interpretation and interpolation of certain specific road building materials, their use in this manner has been limited to a few special cases. This thesis sets out to show that under certain conditions, which pertain in many regions of the world, airphoto interpretation can be used for the direct location of 1materials possessing particular engineering characteristics. Further, it sets out to show, that this can be done for the full range of engineering properties required of materials for all the significant layers of construction, despite the fact that the materials involved may be of widely differing composition and geological origin. The actual interpretation is based on the fundamental recognition of the elements of form, tone, and texture making up the total photographic pattern. Similar features reflected on photographs are shown to be comprised of similar materials, not merely geologically speaking, but more especially in respect of their significant engineering characteristics; it is still further demonstrated that this is applicable even when such features are situated some considerable distance apart. Variations of notable engineering importance within one and the same geological occurrence, are also shown to be identifiable on the aerial photographs. For major road projects in areas subjected to certain environmental conditions, these possibilities form the basis of a new prospecting technique, which incorporates the full use of the science or art of interpretation. The basic concept governing the applicability of this technique and the steps necessary to ensure the development of the full potential of aerial photography in its application, are discussed and illustrated by detailed accounts of a number of specific projects. These projects incorporate both materials appraisals of wide strips of country for route location purposes and intensive prospecting along chosen routes. The techniques thus developed, constitute a new approach to materials investigations for major road projects and in this respect contribute to knowledge in this field. Finally, conclusions are drawn on the relative merits of materials investigation methods in current use in South West Africa and on how these methods affect the different organisations involved in the planning and construction of major road projects. The use made of airphoto interpretation for similar engineering works in other countries, as well as the possible future scope for the application of the particular method of materials investigation described in this thesis, are also covered.

The purpose of the study was to construct and validate a wall volley test to be used in determining one's over-all playing ability in aerial tennis. The specific problem was to determine the reliability and validity of the wall volley test.

The Art and Craft of Aerial Dance discusses my personal experiences training and performing aerial dance, along with my study of safe practices in aerial rigging. My journey as a Theatre and Dance Honors-In-Discipline Scholar at East Tennessee State University from 2016-2020, culminated with my senior thesis capstone performance at Azure Aerial Arts on Friday, December 6th, 2019. This exploration into the world of aerial dance began in the spring of 2017 and has not ceased. If anything, the drive and motivation to continue pushing forward despite many obstacles continues to grow and manifest itself into new forms in my life. This drive, and my work as an intern with Night Owl Circus Arts (NOCA) at Azure Aerial Arts over the summer of 2019, propelled me to choose this topic as my final thesis because of all of my accomplishments at ETSU, this is one that I hold nearest and dearest to my heart.

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As the use of Unmanned Aerial Systems (UAS) becomes more common in both civilian/commercial and military applications, so too has the risk of injury to individuals and third parties on the ground. The purpose of this research is to further enhance methods currently in use for performing flight path risk assessment for UAS, as well as improve upon an existing software tool: Quantitative Approach and Departure Risk Assessment (QUADRA). The primary focus is upon the incorporation of building information to determine the protection offered to sheltered populations, reevaluate the probability of fatality models used in aircraft failures to more accurately determine the risk for smaller UAS systems, and to provide a metric for determining the number of individuals that are adversely affected by the noise of the autonomous system as it performs its mission. / Master of Science / Unmanned Aerial Vehicles are aircraft that are operated without a pilot onboard. More conventionally known as drones, these aircraft can be at increased risk to individuals on the ground as there is no pilot in the aircraft to course correct should the aircraft fail. Due to the potential for drones to fail and thus injure people on the ground, a method for determining the number of people injured or killed by an aircraft for its mission has been developed. These methods identify areas on the ground where the aircraft may land, as well as the potential number of fatalities for a given mission. To minimize the risk to people on the ground, the flight path of the drone is changed until a lower risk flight path is found. Similarly, the sound produced by these drones is used to determine the number of people who may hear the aircraft as it is flying overhead, as well as the number of people who may be annoyed or disturbed by this noise.

No description available.