by Fung Wai Keung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 146-151). / Acknowledgements --- p.viii / Abstract --- p.1 / Chapter 1 --- Overview --- p.3 / Chapter 1.1 --- Tactile Sensing in Human and Robot --- p.4 / Chapter 1.1.1 --- Human Hands and Robotic Hands --- p.4 / Chapter 1.1.2 --- Mechanoreceptors in skin and Tactile Sensor Arrays --- p.7 / Chapter 1.2 --- Motivation --- p.12 / Chapter 1.3 --- Objectives --- p.13 / Chapter 1.4 --- Related Work --- p.14 / Chapter 1.4.1 --- Using Vision Alone --- p.15 / Chapter 1.4.2 --- Integration of Vision and Touch --- p.15 / Chapter 1.4.3 --- Using Touch Sensing Alone --- p.17 / Chapter 1.4.3.1 --- Ronald S. Fearing's Work --- p.18 / Chapter 1.4.3.2 --- Peter K. Allen's Work --- p.22 / Chapter 1.5 --- Outline --- p.26 / Chapter 2 --- Geometric Models --- p.27 / Chapter 2.1 --- Introduction --- p.27 / Chapter 2.2 --- Superquadrics --- p.27 / Chapter 2.2.1 --- 2D Superquadrics --- p.27 / Chapter 2.2.2 --- 3D Superquadrics --- p.29 / Chapter 2.3 --- Model Recovery of Superquadric Models --- p.31 / Chapter 2.3.1 --- Problem Formulation --- p.31 / Chapter 2.3.2 --- Least Squares Optimization --- p.33 / Chapter 2.4 --- Free-Form Deformations --- p.34 / Chapter 2.4.1 --- Bernstein Basis --- p.36 / Chapter 2.4.2 --- B-Spline Basis --- p.38 / Chapter 2.5 --- Other Geometric Models --- p.41 / Chapter 2.5.1 --- Generalized Cylinders --- p.41 / Chapter 2.5.2 --- Hyperquadrics --- p.42 / Chapter 2.5.3 --- Polyhedral Models --- p.44 / Chapter 2.5.4 --- Function Representation --- p.45 / Chapter 3 --- Sensing Strategy --- p.54 / Chapter 3.1 --- Introduction --- p.54 / Chapter 3.2 --- Sensing Algorithm --- p.55 / Chapter 3.2.1 --- Assumption of objects --- p.55 / Chapter 3.2.2 --- Haptic Exploration Procedures --- p.56 / Chapter 3.3 --- Contour Tracing --- p.58 / Chapter 3.4 --- Tactile Sensor Data Preprocessing --- p.59 / Chapter 3.4.1 --- Data Transformation and Sensor Calibration --- p.60 / Chapter 3.4.2 --- Noise Filtering --- p.61 / Chapter 3.5 --- Curvature Determination --- p.64 / Chapter 3.6 --- Step Size Determination --- p.73 / Chapter 4 --- 3D Shape Reconstruction --- p.80 / Chapter 4.1 --- Introduction --- p.80 / Chapter 4.2 --- Correspondence Problem --- p.81 / Chapter 4.2.1 --- Affine Invariance Property of B-splines --- p.84 / Chapter 4.2.2 --- Point Inversion Problem --- p.87 / Chapter 4.3 --- Parameter Triple Interpolation --- p.91 / Chapter 4.4 --- 3D Object Shape Reconstruction --- p.94 / Chapter 4.4.1 --- Heuristic Approach --- p.94 / Chapter 4.4.2 --- Closed Contour Recovery --- p.97 / Chapter 4.4.3 --- Control Lattice Recovery --- p.102 / Chapter 5 --- Implementation --- p.105 / Chapter 5.1 --- Introduction --- p.105 / Chapter 5.2 --- Implementation Tool - MATLAB --- p.105 / Chapter 5.2.1 --- Optimization Toolbox --- p.107 / Chapter 5.2.2 --- Splines Toolbox --- p.108 / Chapter 5.3 --- Geometric Model Implementation --- p.109 / Chapter 5.3.1 --- FFD Examples --- p.111 / Chapter 5.4 --- Shape Reconstruction Implementation --- p.112 / Chapter 5.5 --- 3D Model Reconstruction Examples --- p.120 / Chapter 5.5.1 --- Example 1 --- p.120 / Chapter 5.5.2 --- Example 2 --- p.121 / Chapter 6 --- Conclusion --- p.128 / Chapter 6.1 --- Future Work --- p.129 / Appendix --- p.133 / Bibliography --- p.146

Cheung Man-Tai. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves 81-84). / Abstracts in English and Chinese. / List of Figures --- p.vi / List of Tables --- p.viii / Chapter Chapter 1. --- Introduction --- p.1 / Chapter 1.1. --- Background --- p.1 / Chapter 1.1.1. --- Parallax --- p.2 / Chapter 1.2. --- Literature Review --- p.3 / Chapter 1.3. --- Research Objective --- p.6 / Chapter 1.4. --- Organization of Thesis --- p.6 / Chapter Chapter 2. --- The 3-Image Algorithm --- p.1 / Chapter 2.1. --- Projective Reconstruction --- p.10 / Chapter 2.2. --- Epipolar Geometry and Fundamental Matrix --- p.11 / Chapter 2.3. --- Determine the Projective Mapping --- p.12 / Chapter 2.3.1. --- Conditions for Initial Matches --- p.13 / Chapter 2.3.2. --- Obtaining the Feature Correspondence --- p.17 / Chapter 2.4. --- Registering Pixel Element --- p.21 / Chapter 2.4.1. --- Single Homography Approach --- p.22 / Chapter 2.4.2. --- Multiple Homography Approach --- p.23 / Chapter 2.4.3. --- Triangular Patches Clustering --- p.24 / Chapter 2.4.3.1. --- Delaunay Triangulation --- p.25 / Chapter 2.5. --- Mosaic Construction --- p.29 / Chapter Chapter 3. --- The n-Image Algorithm --- p.31 / Chapter Chapter 4. --- The Uneven-Sampling-Rate n-Image Algorithm --- p.34 / Chapter 4.1. --- Varying the Reference-Target Images Separation --- p.35 / Chapter 4.2. --- Varying the Target-Intermediate Images Separation --- p.38 / Chapter Chapter 5. --- Experiments --- p.43 / Chapter 5.1. --- Experimental Setup --- p.43 / Chapter 5.1.1. --- Measuring the Performance --- p.43 / Chapter 5.2. --- Experiments on the 3-Image Algorithm --- p.44 / Chapter 5.2.1. --- Planar Scene --- p.44 / Chapter 5.2.2. --- Comparison between a Global Parametric Transformation and the 3-Image Algorithm --- p.46 / Chapter 5.2.3. --- Generic Scene --- p.49 / Chapter 5.2.4. --- The Triangular Patches Clustering against the Multiple Homography Approach --- p.52 / Chapter 5.3. --- Experiments on the n-Image Algorithm --- p.56 / Chapter 5.3.1. --- Initial Experiment on the n-Image Algorithm --- p.56 / Chapter 5.3.2. --- Another Experiment on the n-Image Algorithm --- p.58 / Chapter 5.3.3. --- the n-Image Algorithm over a Longer Image Stream --- p.61 / Chapter 5.4. --- Experiments on the Uneven-Sampling-Rate n-Image Algorithm --- p.65 / Chapter 5.4.1. --- Varying Reference-Target Images Separation --- p.65 / Chapter 5.4.2. --- Varying Target-Intermediate Images Separation --- p.69 / Chapter 5.4.3. --- Comparing the Uneven-Sampling-Rate n-Image Algorithm and Global Transformation Method --- p.73 / Chapter Chapter 6. --- Conclusion and Discussion --- p.76 / Bibliography --- p.81

Xie, Yongming. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 77-85). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.ii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Isosurfaces --- p.1 / Chapter 1.2 --- Graphics Processing Unit --- p.2 / Chapter 1.3 --- Objective --- p.3 / Chapter 1.4 --- Contribution --- p.3 / Chapter 1.5 --- Thesis Organization --- p.4 / Chapter 2 --- Marching Cubes --- p.5 / Chapter 2.1 --- Introduction --- p.5 / Chapter 2.2 --- Marching Cubes Algorithm --- p.7 / Chapter 2.3 --- Triangulated Cube Configuration Table --- p.12 / Chapter 2.4 --- Summary --- p.16 / Chapter 3 --- Graphics Processing Unit --- p.18 / Chapter 3.1 --- Introduction --- p.18 / Chapter 3.2 --- History of Graphics Processing Unit --- p.19 / Chapter 3.2.1 --- First Generation GPU --- p.20 / Chapter 3.2.2 --- Second Generation GPU --- p.20 / Chapter 3.2.3 --- Third Generation GPU --- p.20 / Chapter 3.2.4 --- Fourth Generation GPU --- p.21 / Chapter 3.3 --- The Graphics Pipelining --- p.21 / Chapter 3.3.1 --- Standard Graphics Pipeline --- p.21 / Chapter 3.3.2 --- Programmable Graphics Pipeline --- p.23 / Chapter 3.3.3 --- Vertex Processors --- p.25 / Chapter 3.3.4 --- Fragment Processors --- p.26 / Chapter 3.3.5 --- Frame Buffer Operations --- p.28 / Chapter 3.4 --- GPU CPU Analogy --- p.31 / Chapter 3.4.1 --- Memory Architecture --- p.31 / Chapter 3.4.2 --- Processing Model --- p.32 / Chapter 3.4.3 --- Limitation of GPU --- p.33 / Chapter 3.4.4 --- Input and Output --- p.34 / Chapter 3.4.5 --- Data Readback --- p.34 / Chapter 3.4.6 --- FramebufFer --- p.34 / Chapter 3.5 --- Summary --- p.35 / Chapter 4 --- Volume Rendering --- p.37 / Chapter 4.1 --- Introduction --- p.37 / Chapter 4.2 --- History of Volume Rendering --- p.38 / Chapter 4.3 --- Hardware Accelerated Volume Rendering --- p.40 / Chapter 4.3.1 --- Hardware Acceleration Volume Rendering Methods --- p.41 / Chapter 4.3.2 --- Proxy Geometry --- p.42 / Chapter 4.3.3 --- Object-Aligned Slicing --- p.43 / Chapter 4.3.4 --- View-Aligned Slicing --- p.45 / Chapter 4.4 --- Summary --- p.48 / Chapter 5 --- GPU-Friendly Marching Cubes --- p.49 / Chapter 5.1 --- Introduction --- p.49 / Chapter 5.2 --- Previous Work --- p.50 / Chapter 5.3 --- Traditional Method --- p.52 / Chapter 5.3.1 --- Scalar Volume Data --- p.53 / Chapter 5.3.2 --- Isosurface Extraction --- p.53 / Chapter 5.3.3 --- Flow Chart --- p.54 / Chapter 5.3.4 --- Transparent Isosurfaces --- p.56 / Chapter 5.4 --- Our Method --- p.56 / Chapter 5.4.1 --- Cell Selection --- p.59 / Chapter 5.4.2 --- Vertex Labeling --- p.61 / Chapter 5.4.3 --- Cell Indexing --- p.62 / Chapter 5.4.4 --- Interpolation --- p.65 / Chapter 5.5 --- Rendering Translucent Isosurfaces --- p.67 / Chapter 5.6 --- Implementation and Results --- p.69 / Chapter 5.7 --- Summary --- p.74 / Chapter 6 --- Conclusion --- p.76 / Bibliography --- p.77

Text-to-scene generation systems take input in the form of a natural language text and output a 3D scene illustrating the meaning of that text. A major benefit of text-to-scene generation is that it allows users to create custom 3D scenes without requiring them to have a background in 3D graphics or knowledge of specialized software packages. This contributes to making text-to-scene useful in scenarios from creative applications to education. The primary goal of this thesis is to explore how we can use text-to-scene generation in a new way: as a tool to facilitate the elicitation and formal documentation of language. In particular, we use text-to-scene generation (a) to assist field linguists studying endangered languages; (b) to provide a cross-linguistic framework for formally modeling spatial language; and (c) to collect language data using crowdsourcing. As a side effect of these goals, we also explore the problem of multilingual text-to-scene generation, that is, systems for generating 3D scenes from languages other than English. The contributions of this thesis are the following. First, we develop a novel tool suite (the WordsEye Linguistics Tools, or WELT) that uses the WordsEye text-to-scene system to assist field linguists with eliciting and documenting endangered languages. WELT allows linguists to create custom elicitation materials and to document semantics in a formal way. We test WELT with two endangered languages, Nahuatl and Arrernte. Second, we explore the question of how to learn a syntactic parser for WELT. We show that an incremental learning method using a small number of annotated dependency structures can produce reasonably accurate results. We demonstrate that using a parser trained in this way can significantly decrease the time it takes an annotator to label a new sentence with dependency information. Third, we develop a framework that generates 3D scenes from spatial and graphical semantic primitives. We incorporate this system into the WELT tools for creating custom elicitation materials, allowing users to directly manipulate the underlying semantics of a generated scene. Fourth, we introduce a deep semantic representation of spatial relations and use this to create a new resource, SpatialNet, which formally declares the lexical semantics of spatial relations for a language. We demonstrate how SpatialNet can be used to support multilingual text-to-scene generation. Finally, we show how WordsEye and the semantic resources it provides can be used to facilitate elicitation of language using crowdsourcing.

An active-matrix electroluminescent (AMEL) design tool has been developed for the simulation of AMEL display devices. The AMEL design tool is a software package that simulates AMEL device operation using a lumped parameter circuit model. The lumped parameter circuit model is developed primarily to address AMEL power dissipation issues. The AMEL design tool provides a user-friendly approach for investigating the AMEL display device through the AMEL lumped parameter circuit model. The AMEL design tool is programmed in C with a standard Microsoft Windows interface. Three techniques for power reduction have been identified and investigated: increasing the high voltage NDMOS transistor breakdown voltage, parasitic capacitance optimization, and development of a low voltage phosphor. / Graduation date: 1998

Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: scene reconstruction vision, image based rendering, graphics, color consistency, specular objects. Includes bibliographical references (p. 56-57).

Thesis (Ph. D.)--Computing, Georgia Institute of Technology, 2006. / Includes bibliographical references (p. 160-171).

Thesis (Ph. D.)--University of Washington, 2002. / Vita. Includes bibliographical references (leaves 88-92).

Thesis (M.F.A.)--Rochester Institute of Technology, 2010. / Typescript. Includes bibliographical references.

Thesis (M.S. in Modeling, Virtual Environments and Simulation)--Naval Postgraduate School, September 2003. / Thesis advisor(s): Christian J. Darken, Joseph A. Sullivan. Includes bibliographical references (p. 91-92). Also available online.