Phase Unwrapping using Chebyshev Polynomials

Phase unwrapping is an intermediate step for interferogram analysis. The phase associated with an interferogram can be estimated using a curve mesh of functions. Each of these functions can be approximated by a linear combination of basis functions. Chebyshev polynomials in addition to being a family of orthogonal polynomials can be defined recursively. In this work a method for phase unwrapping using Chebyshev polynomials is proposed. Results show good performance when applied to synthetic images without noise and also to synthetic images with noise

An investigation of methods of surface estimation with application to the interpolation of antenna patterns

The problem of estimating a surface from a set of discrete measurements lying along straight lines is considered. This situation arises when one attempts to determine the S-Band antenna gain pattern for the Space Shuttle, from measurements taken at several ground stations. The results of previous investigators concerned with the performance of surface approximation techniques for the present application, are extended in this study by examining the case where the data samples are corrupted by measurement noise. Results have been obtained using least-squares approximation with bicubic B-spline basis functions, and for an interpolation algorithm in conjunction with a spatial smoothing filter. Because of the nature of the data acquisition and the impracticality of the least-squares algorithm when many sample points are used, the application of the Kalman filter to the surface estimation problem is discussed, although no numerical results were obtained using this approach. It is shown that a direct application of Kalman filter theory yields a filter algorithm which would be extremely difficult to implement. Based on the applications of reduced-order, suboptimal filters to image processing, a suboptimal approximation to the Kalman filter, applied to the surface estimation problem, is considered. The use of a decentralized estimation approach to this problem is briefly examined --Abstract, page ii

Accelerating Reinforcement Learning by Composing Solutions of Automatically Identified Subtasks

This paper discusses a system that accelerates reinforcement learning by using transfer from related tasks. Without such transfer, even if two tasks are very similar at some abstract level, an extensive re-learning effort is required. The system achieves much of its power by transferring parts of previously learned solutions rather than a single complete solution. The system exploits strong features in the multi-dimensional function produced by reinforcement learning in solving a particular task. These features are stable and easy to recognize early in the learning process. They generate a partitioning of the state space and thus the function. The partition is represented as a graph. This is used to index and compose functions stored in a case base to form a close approximation to the solution of the new task. Experiments demonstrate that function composition often produces more than an order of magnitude increase in learning rate compared to a basic reinforcement learning algorithm

Computer Graphics Learning Materials

Selles lõputöös on antud ülevaade Tartu Ülikooli aine Arvutigraafika (MTAT.03.015) jaoks koostatud õppematerjalist ja õppekeskkonnast. Kirjeldatud on aine modulaarset ülesehitust, mis rakendab kombineeritud ülevalt-alla (ing. k. top-down) ja alt-üles (ing. k. bottom-up) lähenemisi. Loodud õppematerjal sisaldab endas interaktiivseid näiteid, mis vastavad hõivatuse taksonoomia 4ndale tasemele. Õppekeskkonna CGLearn spetsifikatsioon ja implementatsiooni detailid on kirjeldatud. Töö lõpus on kursusel osalenud õpilaste hulgas läbi viidud tagasiside küsitluse tulemuste analüüsiga. Lisa fail on lingina kätesaadav serveri probleemide tõttu aadresil : http://comserv.cs.ut.ee/forms/ati_report/files/ComputerGraphicsLearningMaterialsAppendix.zipThis thesis provides an overview of the learning material and a custom learning environment created for the Computer Graphics (MTAT.03.015) course in the University of Tartu. It describes a modular layout, that mixes a top-down and bottom-up approaches, in which the course was organized. The created material also includes interactive examples that satisfy engagement level 4 requirements. The specification and implementation details of the custom learning environment called CGLearn are given. Thesis concludes with the analysis of the feedback questionnaire answered by the students participating in the course and using the material. Due to server problems extras file is in here : http://comserv.cs.ut.ee/forms/ati_report/files/ComputerGraphicsLearningMaterialsAppendix.zi

Final Report to NSF of the Standards for Facial Animation Workshop

The human face is an important and complex communication channel. It is a very familiar and sensitive object of human perception. The facial animation field has increased greatly in the past few years as fast computer graphics workstations have made the modeling and real-time animation of hundreds of thousands of polygons affordable and almost commonplace. Many applications have been developed such as teleconferencing, surgery, information assistance systems, games, and entertainment. To solve these different problems, different approaches for both animation control and modeling have been developed

Learning from the Artist: Theory and Practice of Example-Based Character Deformation

Movie and game production is very laborious, frequently involving hundreds of person-years for a single project. At present this work is difficult to fully automate, since it involves subjective and artistic judgments. Broadly speaking, in this thesis we explore an approach that works with the artist, accelerating their work without attempting to replace them. More specifically, we describe an “example-based” approach, in which artists provide examples of the desired shapes of the character, and the results gradually improve as more examples are given. Since a character’s skin shape deforms as the pose or expression changes, or particular problem will be termed character deformation. The overall goal of this thesis is to contribute a complete investigation and development of an example-based approach to character deformation. A central observation guiding this research is that character animation can be formulated as a high-dimensional problem, rather than the two- or three-dimensional viewpoint that is commonly adopted in computer graphics. A second observation guiding our inquiry is that statistical learning concepts are relevant. We show that example-based character animation algorithms can be informed, developed, and improved using these observations. This thesis provides definitive surveys of example-based facial and body skin deformation. This thesis analyzes the two leading families of example-based character deformation algorithms from the point of view of statistical regression. In doing so we show that a wide variety of existing tools in machine learning are applicable to our problem. We also identify several techniques that are not suitable due to the nature of the training data, and the high-dimensional nature of this regression problem. We evaluate the design decisions underlying these example-based algorithms, thus providing the groundwork for a ”best practice” choice of specific algorithms. This thesis develops several new algorithms for accelerating example-based facial animation. The first algorithm allows unspecified degrees of freedom to be automatically determined based on the style of previous, completed animations. A second algorithm allows rapid editing and control of the process of transferring motion capture of a human actor to a computer graphics character. The thesis identifies and develops several unpublished relations between the underlying mathematical techniques. Lastly, the thesis provides novel tutorial derivations of several mathematical concepts, using only the linear algebra tools that are likely to be familiar to experts in computer graphics. Portions of the research in this thesis have been published in eight papers, with two appearing in premier forums in the field

Manufacturing and Evaluation of a Biologically Inspired Engineered MAV Wing Compared to the Manduca Sexta Wing Under Simulated Flapping Conditions

In recent years, researchers have expressed a vested interest in the concepts surrounding flapping wing micro air vehicles (FWMAVs) that are capable of both range and complex maneuvering. Most research in this arena has found itself concentrated on topics such as flapping dynamics and the associated fluid-structure interactions inherent in the motion, however there still remains myriad questions concerning the structural qualities intrinsic to the wings themselves. Using nature as the template for design, FWMAV wings were constructed using carbon fiber and Kapton and tested under simplified flapping conditions by analyzing frozen\u27 digital images of the deformed wing by methods of photogrammetry. This flapping motion was achieved via the design and construction of a flapper that emulates several of the kinematic features that can be seen in naturally occurring flyers. The response to this motion was then compared to the inspiring specimen\u27s wings, the North American Hawkmoth (Manduca Sexta), under the same flapping conditions in order to identify some of the key features that nature has deemed necessary for successful flight

Electromagnetic containerless processing requirements and recommended facility concept and capabilities for space lab

Containerless melting, reaction, and solidification experiments and processes which potentially can lead to new understanding of material science and production of new or improved materials in the weightless space environment are reviewed in terms of planning for spacelab. Most of the experiments and processes discussed are amenable to the employment of electromagnetic position control and electromagnetic induction or electron beam heating and melting. The spectrum of relevant properties of materials, which determine requirements for a space laboratory electromagnetic containerless processing facility are reviewed. Appropriate distributions and associated coil structures are analyzed and compared on the basis of efficiency, for providing the functions of position sensing, control, and induction heating. Several coil systems are found capable of providing these functions. Exchangeable modular coils in appropriate sizes are recommended to achieve the maximum power efficiencies, for a wide range of specimen sizes and resistivities, in order to conserve total facility power