A dissertation submitted for the fulfilment of the requirements of the degree of Master of Science to the Faculty of Science, Witwatersrand University, Johannesburg. June 2016. / The combination of effective numerical techniques and scientific intuition to find new and novel types of materials is the process used in the discovery of materials for future technologies. Adding to that, being able to calculate the radiative lifetimes of excitons, exciton properties, and the optical properties by using efficient numerical techniques gives an estimation and identification of the best candidate materials for a solar cell. This approach is inexpensive and stable. Present ab initio methods based on Many-body perturbation theory and density functional theory are capable of predicting these properties with a high enough level of accuracy for most cases. The electronic properties calculated using GaAs as a reference system and the 3D hybird perovskite CH3NH3PbI3 are based on density functional theory. The optical properties are investigated by calculating the dielectric function. The theoretical framework of the radiative lifetime of excitons and calculating the exciton properties are based on Wannier model of the exciton and the Bethe-Salpeter equation. / MT2017

A dissertation submitted to the Faculty of Arts, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Arts May 2016 / The technology of 3-D Printing is afforded extensive coverage in the media. Discourses surrounding this technology are charged with ideas of revolutions in manufacturing, democratisation of technology, and the potential to change the face of consumption and production. This technology is being marketed to the consumer and hobbyist. The consumer-grade 3-D printer is a result of the labour of a loose-knit worldwide community of hobbyists known as the "Maker movement". This movement, a convergence of the traditional "Hacker" culture and Do It Yourself (DIY) is constructed around ideas of affective labour. That is, labour performed for the sole purpose of enjoyment of doing so, and for a sense of well-being and community. The explosion of "affordable" 3-D printing as a technology is a result of this affective labour, yet little mention is made of any forms of labour in popular media discourses surrounding this technology. In this paper I construct a history of the Maker movement while theorising the forms of labour inherent to this movement using the Autonomist Marxism of Michael Hardt and Antonio Negri as a framework. Then, working within the field of Cultural Studies, and drawing on Actor-Network Theory (ANT), I perform Multimodal Critical Discourse Analysis (MCDA) on a small sample of texts to illustrate the occlusion and obfuscation of labour within these discourses of the consumer 3-D printer

Acquiring 3-D motion of a camera from image sequences is one of the key components in a wide range of applications such as human computer interaction. Given the 3-D structure, the problem of camera motion recovery can he solved using the model-based approaches, which are well-known and have good performance under a controlled environment. If prior information on the scene is not available, traditional Structure from Motion (SFM) algorithms, which simultaneously estimate the scene structure and pose information, are required. The research presented in this thesis belongs to a different category: Motion from Motion (MFM), in which the main concern is the camera position and orientation. To be more precise, MFM algorithms have the capability of estimating 3-D camera motion directly from 2-D image motion without the explicit reconstruction of the scene structure, even though the 3-D model structure is not known in prior. As keeping track of the structural information is no longer required, putting these types of algorithms into real applications is relatively easy and convenient. / It is demonstrated in the experiments that the proposed algorithms are efficient, stable and accurate compared to several existing approaches. Furthermore, they have been put into applications such as mixed reality, virtual reality, robotics and super-resolution to show their performance in real situations. / The objective of this thesis is to develop a high-speed recursive approach that tackles the MFM problem. On the way to the final goal, a series of methods, each having its own strengths and characteristics, have been studied. (1) The first algorithm computes the camera pose from a monocular image sequence. The trifocal tensor is incorporated into the Extended Kalman Filter (EKF) formulation. The step of computing the 3-D models can thus be eliminated. (2) The proposed approach is then extended to the recovery of motion from a stereo image sequence. By applying the trifocal tensor to a stereo vision framework, the trifocal constraint becomes more robust and is not likely to be degenerate. In addition, the twist motion model is adopted to parameterize the 3-D motion. It does not suffer from singularities as Euler angles, and is minimal as opposed to quaternion and the direct use of rotation matrix. (3) The third method introduces the Interacting Multiple Model Probabilistic Data Association Filter (IMMPDAF) to the MFM problem. The Interacting Multiple Model (IMM) technique allows the existence of more than one dynamic system and in return leads to improved accuracy and stability even under abrupt motion changes. The Probabilistic Data Association (PDA) framework makes the automatic selection of measurement sets possible, resulting in enhanced robustness to occlusions and moving objects. As the PDA associates stereo correspondences probabilistically, the explicit establishment of stereo matches is not necessary except during initialization, and the point features present in the outer region of the stereo images can be utilized. / Yu, Ying Kin. / "July 2007." / Adviser: Wong Kin Hong. / Source: Dissertation Abstracts International, Volume: 69-02, Section: B, page: 1125. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (p. 120-130). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract in English and Chinese. / School code: 1307.

by Andrew Poon Ngai Ho. / Thesis (M.S.)--Chinese University of Hong Kong, 1993. / Includes bibliographical references (leaves [97-98]). / ABSTRACT / ACKNOWLEDGMENTS / Chapter 1. --- INTRODUCTION / Chapter 2. --- REPRESENTATION OP SPEECH DATA --- p.4 / Chapter 2.1 --- SAMPLE DATA REPRESENTATION --- p.4 / Chapter 2.2 --- ANALOG LINEAR SYSTEM MODEL --- p.7 / Chapter 2.3 --- DISCRETE FOURIER TRANSFORM --- p.8 / Chapter 2.4 --- FILTER BAND REPRESENTATION --- p.8 / Chapter 2.5 --- LINEAR PREDICTIVE CODING (LPC) --- p.10 / Chapter 2.2 --- LPC CEPSTRAL COEFFICIENT --- p.13 / Chapter 3. --- MULTI-DIMENSIONAL ANALYSIS --- p.18 / Chapter 3.1 --- PURE GRAPHICAL TOOLS --- p.18 / Chapter 3.1.1 --- MULTI-HISTOGRAM --- p.18 / Chapter 3.1.2 --- STARS --- p.19 / Chapter 3.1.3 --- SPIKED SCATTERPLOT --- p.19 / Chapter 3.1.4 --- GLYPHS --- p.22 / Chapter 3.1.5 --- BOXES --- p.22 / Chapter 3.1.6 --- LIMITATIONS OF THE BASIC METHODS --- p.22 / Chapter 3.1.7 --- CHERNOFF FACES --- p.26 / Chapter 3.1.8 --- ANDREW'S CURVE --- p.27 / Chapter 3.1.9 --- LIMITATIONS OF CHERNOFF FACES AND ANDREW'S CURVE --- p.30 / Chapter 3.1.10 --- SCATTERED PLOT MATRIX --- p.30 / Chapter 3.1.11 --- PARALLEL-AXIS SYSTEM --- p.32 / Chapter 3.1.12 --- COMMON BASIC PITFALL --- p.33 / Chapter 3.2 --- PURE PROJECTION METHODS --- p.36 / Chapter 3.2.1 --- PRINCIPAL COMPONENTS ANALYSIS --- p.36 / Chapter 3.2.2 --- PRINCIPLE CO-ORDINATES ANALYSIS --- p.37 / Chapter 3.2.3 --- REGRESSION ANALYSIS --- p.38 / Chapter 3.3 --- SLICED INVERSE REGRESSION (SIR) --- p.41 / Chapter 4 --- DATA ANALYSIS --- p.50 / Chapter 4.1 --- PROGRAMS AND TEST DATA --- p.50 / Chapter 4.2 --- ACTUAL SPEECH DATA RESULTS --- p.63 / Chapter 4.2.1 --- "SINGLE UTTERANCE OF ""4"" BY SPEAKER A ONLY" --- p.66 / Chapter 4.2.2 --- "TWELVE UTTERANCES OF ""4"" BY SPEAKER A" --- p.72 / Chapter 4.2.3 --- "THREE UTTERANCES PER SPEAKER OF ""4"" BY SPEAKER A, B AND C" --- p.78 / Chapter 4.2.4 --- "TWO UTTERANCES PER DIGIT OF ""1"" TO ""9"" BY SPEAKER A" --- p.83 / Chapter 4.2.5 --- "ONE UTTERANCE PER DIGIT PER SPEAKER OF ""1"" TO ""9"" BY SPEAKER A,B,C" --- p.86 / CONCLUSION AND FURTHER WORKS --- p.93 / Chapter 5.1 --- CONCLUSION --- p.93 / Chapter 5.2 --- FURTHER WORKS --- p.94 / REFERENCES / APPENDIX I MATLAB PROGRAM LISTING FOR SIR / APPENDIX 2 C PROGRAM LISTING FOR ROTATIONAL VIEW / APPENDIX 3 C PROGRAM LISTING FOR LPC AND CEPSTRAL TRANSFORMS / "APPENDIX 4 ALL VIEWS, EIGENVALUES AND EIGENVECTORS FOR SINGLE UTTERANCE OF ""4"" BY SPEAKER A" / "APPENDIX 5 ALL VIEWS, EIGENVALUES AND EIGENVECTORS FOR 12 UTTERANCES OF ""4"" BY SPEAKER A" / "APPENDIX 6 ALL VIEWS, EIGENVALUES AND EIGENVECTORS FOR 5 UTTERANCES PER SPEAKER OF ""4"" BY SPEAKER A,B,C" / "APPENDIX 7 ALL VIEWS, EIGENVALUES AND EIGENVECTORS FOR 2 UTTERANCES PER DIGIT OF DIGIT ""l"" TO ""9"" BY SPEAKER A" / "APPENDIX 8 ALL VIEWS, EIGENVALUES AND EIGENVECTORS FOR 1UTTERANCE PER SPEAKER PER DIGIT OF ""1"" TO ""9"" BY SPEAKER A,B,C"

by Tin Pong. / Thesis (M.Sc.)--Chinese University of Hong Kong, 1994. / Includes bibliographical references (leaf 73). / Abstract --- p.2 / Acknowledgement --- p.4 / Table of Contents --- p.5 / Chapter I. --- Introduction --- p.8 / Chapter II. --- Segmentation Tools --- p.11 / Chapter 2.1. --- Segmentation of Object --- p.11 / Chapter 2.1.1. --- Segmentation algorithm --- p.11 / Chapter 2.1.2. --- Region growing algorithm --- p.16 / Chapter 2.2. --- Noise Reduction --- p.19 / Chapter 2.2.1. --- Median filtering --- p.19 / Chapter 2.2.2 --- Mean filtering --- p.20 / Chapter 2.3. --- Other functions --- p.21 / Chapter 2.3.1. --- Contrast enhancement and reduction --- p.21 / Chapter 2.3.2. --- Brightness increment and reduction --- p.22 / Chapter III. --- 3D Visualization Tools --- p.23 / Chapter 3.1. --- Interpolation --- p.23 / Chapter 3.1.1. --- Estimate distance between slices --- p.23 / Chapter 3.1.2. --- Trilinear Interpolation --- p.24 / Chapter 3.2. --- Projection --- p.26 / Chapter 3.2.1. --- Parallel projection --- p.26 / Chapter 3.2.2. --- Z-Buffers --- p.27 / Chapter 3.3. --- Rotation of 3D image --- p.29 / Chapter 3.4. --- Shading --- p.30 / Chapter IV. --- Description of the software developed --- p.32 / Chapter 4.1. --- Programming environment --- p.32 / Chapter 4.2. --- Software developed --- p.32 / Chapter 4.3. --- 2D object segmentation panel --- p.35 / Chapter 4.4. --- 3D object segmentation panel --- p.45 / Chapter V. --- Results and analysis --- p.56 / Chapter 5.1. --- Results of segmentation of object --- p.56 / Chapter 5.2. --- Results of 3D visualization tools --- p.64 / Chapter VI. --- Future Development --- p.70 / Chapter VII. --- Conclusion --- p.72 / References --- p.73

Wai-kin Vong. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1994. / Includes bibliographical references (leaves 87-[91]). / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Three Dimensional Image --- p.1 / Chapter 1.2 --- Definition of segmentation --- p.2 / Chapter 1.3 --- 3D Image Segmentation --- p.3 / Chapter 1.4 --- Image Splitting Operation --- p.4 / Chapter 1.5 --- Region Merging Operation --- p.4 / Chapter 1.6 --- Split-and-merge Segmentation --- p.4 / Chapter 1.6.1 --- Selection of particular operators --- p.5 / Chapter 2 --- Overview of Image Segmentation Techniques --- p.6 / Chapter 2.1 --- Introduction --- p.6 / Chapter 2.2 --- Edge Based Method --- p.6 / Chapter 2.2.1 --- 3D Laplacian of Gaussian Filtering --- p.7 / Chapter 2.2.2 --- 3D Deformable Surfaces [8] --- p.11 / Chapter 2.3 --- Region Based Method --- p.14 / Chapter 2.3.1 --- 3D oct-tree split-and-merge --- p.15 / Chapter 2.3.2 --- 3D pyramid segmentation --- p.17 / Chapter 2.4 --- 2D segmentation Approaches --- p.20 / Chapter 2.4.1 --- 2D Image segmentation by shape description --- p.20 / Chapter 2.4.2 --- Morphological Watershed Transform (WT) --- p.23 / Chapter 2.5 --- Discussion --- p.34 / Chapter 3 --- Modification Of Digital Watershed Transform (DWT) --- p.36 / Chapter 3.1 --- Introduction --- p.36 / Chapter 3.2 --- Edge Detection --- p.37 / Chapter 3.2.1 --- Discrete Non-linear Edge Detectors --- p.37 / Chapter 3.2.2 --- Canny's Edge Detector --- p.40 / Chapter 3.2.3 --- Gradient of Gaussian Filter --- p.42 / Chapter 3.3 --- Digital Watershed Transform --- p.46 / Chapter 3.3.1 --- Introduction --- p.46 / Chapter 3.3.2 --- Modification of SKIZ --- p.46 / Chapter 3.3.3 --- Implementation --- p.51 / Chapter 4 --- Region Modeling --- p.55 / Chapter 4.1 --- Introduction --- p.55 / Chapter 4.2 --- Texture Definition --- p.57 / Chapter 4.3 --- Texture Modeling --- p.58 / Chapter 4.3.1 --- Markov Random Field (MRF) --- p.58 / Chapter 4.3.2 --- Simultaneous Autoregressive (SAR) Model --- p.59 / Chapter 4.3.3 --- Parameter Estimation --- p.61 / Chapter 4.3.4 --- A Simple model --- p.63 / Chapter 4.3.5 --- Combination of MRF parameters --- p.63 / Chapter 4.3.6 --- Similarity Measure --- p.66 / Chapter 4.4 --- Model Evaluation --- p.68 / Chapter 4.4.1 --- Classification of Different Materials --- p.68 / Chapter 4.4.2 --- Rotational Invariance --- p.69 / Chapter 4.5 --- Results and Observations --- p.72 / Chapter 5 --- Three-Dimensional Segmentation with Interactive Labeling --- p.73 / Chapter 5.1 --- Introduction --- p.73 / Chapter 5.2 --- Region Merging Scheme --- p.75 / Chapter 5.3 --- Interactive Labeling --- p.76 / Chapter 5.4 --- Experiment of 3D Guided Segmentation --- p.77 / Chapter 6 --- Conclusion --- p.81 / Chapter 6.1 --- Image Partitioning by Watershed Transform --- p.81 / Chapter 6.2 --- Image modeling by Markov Random Field --- p.82 / Chapter 6.3 --- 3D image segmentation --- p.82 / A --- p.84 / B --- p.86 / Bibliography --- p.87

Cheung Man-kin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 116-120). / Abstracts in English and Chinese. / Chapter 1) --- Introduction --- p.1 / Chapter 1.1) --- Building of the 3D Wireframe and Facial Model --- p.2 / Chapter 1.2) --- Description of 3D Model Based Video Conferencing --- p.3 / Chapter 1.3) --- Wireframe Model Fitting or Conformation --- p.6 / Chapter 1.4) --- Pose Estimation --- p.8 / Chapter 1.5) --- Facial Motion Estimation and Synthesis --- p.9 / Chapter 1.6) --- Thesis Outline --- p.10 / Chapter 2) --- Wireframe model Fitting --- p.11 / Chapter 2.1) --- Algorithm of WFM Fitting --- p.12 / Chapter 2.1.1) --- Global Deformation --- p.14 / Chapter a) --- Scaling --- p.14 / Chapter b) --- Shifting --- p.15 / Chapter 2.1.2) --- Local Deformation --- p.15 / Chapter a) --- Shifting --- p.16 / Chapter b) --- Scaling --- p.17 / Chapter 2.1.3) --- Fine Updating --- p.17 / Chapter 2.2) --- Steps of Fitting --- p.18 / Chapter 2.3) --- Functions of Different Deformation --- p.18 / Chapter 2.4) --- Experimental Results --- p.19 / Chapter 2.4.1) --- Output wireframe in each step --- p.19 / Chapter 2.4.2) --- Examples of Mis-fitted wireframe with incoming image --- p.22 / Chapter 2.4.3) --- Fitted 3D facial wireframe --- p.23 / Chapter 2.4.4) --- Effect of mis-fitted wireframe after compensation of motion --- p.24 / Chapter 2.5) --- Summary --- p.26 / Chapter 3) --- Epipolar Geometry --- p.27 / Chapter 3.1) --- Pinhole Camera Model and Perspective Projection --- p.28 / Chapter 3.2) --- Concepts in Epipolar Geometry --- p.31 / Chapter 3.2.1) --- Working with normalized image coordinates --- p.33 / Chapter 3.2.2) --- Working with pixel image coordinates --- p.35 / Chapter 3.2.3) --- Summary --- p.37 / Chapter 3.3) --- 8-point Algorithm (Essential and Fundamental Matrix) --- p.38 / Chapter 3.3.1) --- Outline of the 8-point algorithm --- p.38 / Chapter 3.3.2) --- Modification on obtained Fundamental Matrix --- p.39 / Chapter 3.3.3) --- Transformation of Image Coordinates --- p.40 / Chapter a) --- Translation to mean of points --- p.40 / Chapter b) --- Normalizing transformation --- p.41 / Chapter 3.3.4) --- Summary of 8-point algorithm --- p.41 / Chapter 3.4) --- Estimation of Object Position by Decomposition of Essential Matrix --- p.43 / Chapter 3.4.1) --- Algorithm Derivation --- p.43 / Chapter 3.4.2) --- Algorithm Outline --- p.46 / Chapter 3.5) --- Noise Sensitivity --- p.48 / Chapter 3.5.1) --- Rotation vector of model --- p.48 / Chapter 3.5.2) --- The projection of rotated model --- p.49 / Chapter 3.5.3) --- Noisy image --- p.51 / Chapter 3.5.4) --- Summary --- p.51 / Chapter 4) --- Pose Estimation --- p.54 / Chapter 4.1) --- Linear Method --- p.55 / Chapter 4.1.1) --- Theory --- p.55 / Chapter 4.1.2) --- Normalization --- p.57 / Chapter 4.1.3) --- Experimental Results --- p.58 / Chapter a) --- Synthesized image by linear method without normalization --- p.58 / Chapter b) --- Performance between linear method with and without normalization --- p.60 / Chapter c) --- Performance of linear method under quantization noise with different transformation components --- p.62 / Chapter d) --- Performance of normalized case without transformation in z- component --- p.63 / Chapter 4.1.4) --- Summary --- p.64 / Chapter 4.2) --- Two Stage Algorithm --- p.66 / Chapter 4.2.1) --- Introduction --- p.66 / Chapter 4.2.2) --- The Two Stage Algorithm --- p.67 / Chapter a) --- Stage 1 (Iterative Method) --- p.68 / Chapter b) --- Stage 2 ( Non-linear Optimization) --- p.71 / Chapter 4.2.3) --- Summary of the Two Stage Algorithm --- p.72 / Chapter 4.2.4) --- Experimental Results --- p.72 / Chapter 4.2.5) --- Summary --- p.80 / Chapter 5) --- Facial Motion Estimation and Synthesis --- p.81 / Chapter 5.1) --- Facial Expression based on face muscles --- p.83 / Chapter 5.1.1) --- Review of Action Unit Approach --- p.83 / Chapter 5.1.2) --- Distribution of Motion Unit --- p.85 / Chapter 5.1.3) --- Algorithm --- p.89 / Chapter a) --- For Unidirectional Motion Unit --- p.89 / Chapter b) --- For Circular Motion Unit (eyes) --- p.90 / Chapter c) --- For Another Circular Motion Unit (mouth) --- p.90 / Chapter 5.1.4) --- Experimental Results --- p.91 / Chapter 5.1.5) --- Summary --- p.95 / Chapter 5.2) --- Detection of Facial Expression by Muscle-based Approach --- p.96 / Chapter 5.2.1) --- Theory --- p.96 / Chapter 5.2.2) --- Algorithm --- p.97 / Chapter a) --- For Sheet Muscle --- p.97 / Chapter b) --- For Circular Muscle --- p.98 / Chapter c) --- For Mouth Muscle --- p.99 / Chapter 5.2.3) --- Steps of Algorithm --- p.100 / Chapter 5.2.4) --- Experimental Results --- p.101 / Chapter 5.2.5) --- Summary --- p.103 / Chapter 6) --- Conclusion --- p.104 / Chapter 6.1) --- WFM fitting --- p.104 / Chapter 6.2) --- Pose Estimation --- p.105 / Chapter 6.3) --- Facial Estimation and Synthesis --- p.106 / Chapter 6.4) --- Discussion on Future Improvements --- p.107 / Chapter 6.4.1) --- WFM Fitting --- p.107 / Chapter 6.4.2) --- Pose Estimation --- p.109 / Chapter 6.4.3) --- Facial Motion Estimation and Synthesis --- p.110 / Chapter 7) --- Appendix --- p.111 / Chapter 7.1) --- Newton's Method or Newton-Raphson Method --- p.111 / Chapter 7.2) --- H.261 --- p.113 / Chapter 7.3) --- 3D Measurement --- p.114 / Bibliography --- p.116

Kwong-Wai, Chen. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 114-118). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgments --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Volumetric Data --- p.1 / Chapter 1.2 --- Volume Visualization --- p.4 / Chapter 1.3 --- Thesis Contributions --- p.5 / Chapter 1.4 --- Thesis Outline --- p.6 / Chapter I --- Multi-body Surface Extraction --- p.8 / Chapter 2 --- Isosurface Extraction --- p.9 / Chapter 2.1 --- Previous Works --- p.10 / Chapter 2.1.1 --- Marching Cubes --- p.10 / Chapter 2.1.2 --- Skeleton Climbing --- p.12 / Chapter 2.1.3 --- Adaptive Skeleton Climbing --- p.14 / Chapter 2.2 --- Motivation --- p.17 / Chapter 3 --- Multi-body Surface Extraction --- p.19 / Chapter 3.1 --- Multi-body Surface --- p.19 / Chapter 3.2 --- Building 0-skeleton --- p.21 / Chapter 3.3 --- Building 1-skeleton --- p.23 / Chapter 3.3.1 --- Non-binary Faces --- p.24 / Chapter 3.3.2 --- Non-binary Cubes --- p.30 / Chapter 3.4 --- General Scheme for Messy Cubes --- p.33 / Chapter 3.4.1 --- Graph Reduction --- p.34 / Chapter 3.4.2 --- Position of the Tetrapoints --- p.36 / Chapter 3.5 --- Triangular Mesh Generation --- p.37 / Chapter 3.5.1 --- Generating the Edge Loops --- p.38 / Chapter 3.5.2 --- Triangulating the Edge Loops --- p.41 / Chapter 3.5.3 --- Incorporating with Adaptive Skeleton Climbing --- p.43 / Chapter 3.6 --- Implementation and Results --- p.45 / Chapter II --- Haptic Rendering of Volumetric Data --- p.60 / Chapter 4 --- Introduction to Haptics --- p.61 / Chapter 4.1 --- Terminology --- p.62 / Chapter 4.2 --- Haptic Rendering Process --- p.63 / Chapter 4.2.1 --- The Overall Process --- p.64 / Chapter 4.2.2 --- Force Profile --- p.65 / Chapter 4.2.3 --- Decoupling Processes --- p.66 / Chapter 4.3 --- The PHANToM´ёØ Haptic Interface --- p.67 / Chapter 4.4 --- Research Goals --- p.69 / Chapter 5 --- Haptic Rendering of Geometric Models --- p.70 / Chapter 5.1 --- Penalty Based Methods --- p.71 / Chapter 5.1.1 --- Vector Fields for Solid Objects --- p.71 / Chapter 5.1.2 --- Drawbacks of Penalty Based Methods --- p.72 / Chapter 5.2 --- Constraint Based Methods --- p.73 / Chapter 5.2.1 --- Virtual Haptic Interface Point --- p.73 / Chapter 5.2.2 --- The Constraints --- p.74 / Chapter 5.2.3 --- Location Computation --- p.78 / Chapter 5.2.4 --- Force Shading --- p.79 / Chapter 5.2.5 --- Adding Surface Properties --- p.80 / Chapter 6 --- Haptic Rendering of Volumetric Data --- p.83 / Chapter 6.1 --- Volume Haptization --- p.84 / Chapter 6.2 --- Isosurface Haptic Rendering --- p.86 / Chapter 6.3 --- Intermediate Representation Approach --- p.89 / Chapter 6.3.1 --- Introduction --- p.89 / Chapter 6.3.2 --- Intermediate Virtual Plane --- p.90 / Chapter 6.3.3 --- Updating Virtual Plane --- p.92 / Chapter 6.3.4 --- Preventing Force Discontinuity Artifacts --- p.93 / Chapter 6.3.5 --- Experiments and Results --- p.94 / Chapter 7 --- Conclusions and Future Research Directions --- p.98 / Chapter 7.1 --- Conclusions --- p.98 / Chapter 7.2 --- Future Research Directions --- p.99 / Chapter A --- Two Proofs of Multi-body Surface Extraction Algorithm --- p.101 / Chapter A.1 --- Graph Terminology and Theorems --- p.101 / Chapter A.2 --- Occurrence of Tripoints in Negative-Positive Pairs --- p.103 / Chapter A.3 --- Validity of the General Scheme --- p.103 / Chapter B --- An Example of Multi-body Surface Extraction Algorithm --- p.105 / Chapter B.1 --- Step 1: Building 0-Skeleton --- p.105 / Chapter B.2 --- Step 2: Building 1-Skeleton --- p.106 / Chapter B.2.1 --- Step 2a: Building 1-Skeleton and Tripoints on Cube Faces --- p.106 / Chapter B.2.2 --- Step 2b: Adding Tetrapoints and Tri-edges inside Cube --- p.106 / Chapter B.3 --- Step 3: Constructing Edge Loops and Triangulating --- p.109 / Bibliography --- p.114

by Andrew L. Arengo. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1998. / Includes bibliographical references (leaves 65-66). / Abstract also in Chinese. / Acknowledgments --- p.ii / List Of Figures --- p.v / Abstract --- p.vii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation and Objective --- p.2 / Chapter 1.2 --- Approach of This Thesis and Contributions --- p.3 / Chapter 1.3 --- Organization of This Thesis --- p.4 / Chapter 2 --- Previous Work --- p.6 / Chapter 2.1 --- Using Grouped Features --- p.6 / Chapter 2.2 --- Applying Additional Heuristics --- p.7 / Chapter 2.3 --- Homography and Related Works --- p.9 / Chapter 3 --- Theory and Problem Formulation --- p.10 / Chapter 3.1 --- Overview of the Problems --- p.10 / Chapter 3.1.1 --- Preprocessing --- p.10 / Chapter 3.1.2 --- Establishing Correspondences --- p.11 / Chapter 3.1.3 --- Recovering 3D Depth --- p.14 / Chapter 3.2 --- Solving the Correspondence Problem --- p.15 / Chapter 3.2.1 --- Epipolar Constraint --- p.15 / Chapter 3.2.2 --- Surface-Continuity and Feature-Ordering Heuristics --- p.16 / Chapter 3.2.3 --- Using the Concept of Homography --- p.18 / Chapter 3.3 --- Concept of Homography --- p.20 / Chapter 3.3.1 --- Barycentric Coordinate System --- p.20 / Chapter 3.3.2 --- Image to Image Mapping of the Same Plane --- p.22 / Chapter 3.4 --- Problem Formulation --- p.23 / Chapter 3.4.1 --- Preliminaries --- p.23 / Chapter 3.4.2 --- Case of Single Planar Surface --- p.24 / Chapter 3.4.3 --- Case of Multiple Planar Surfaces --- p.28 / Chapter 3.5 --- Subspace Clustering --- p.28 / Chapter 3.6 --- Overview of the Approach --- p.30 / Chapter 4 --- Experimental Results --- p.33 / Chapter 4.1 --- Synthetic Images --- p.33 / Chapter 4.2 --- Aerial Images --- p.36 / Chapter 4.2.1 --- T-shape building --- p.38 / Chapter 4.2.2 --- Rectangular Building --- p.39 / Chapter 4.2.3 --- 3-layers Building --- p.40 / Chapter 4.2.4 --- Pentagon --- p.44 / Chapter 4.3 --- Indoor Scenes --- p.52 / Chapter 4.3.1 --- Stereo Motion Pair --- p.53 / Chapter 4.3.2 --- Hallway Scene --- p.56 / Chapter 5 --- Summary and Conclusions --- p.63

by Ho Pui-Kuen, Patrick. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1998. / Includes bibliographical references (leaves 57-59). / Abstract also in Chinese. / Acknowledgments --- p.ii / List Of Figures --- p.v / List Of Tables --- p.vi / Abstract --- p.vii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Moviation of Problem --- p.1 / Chapter 1.2 --- Our Approach and Summary of Contributions --- p.3 / Chapter 1.3 --- Organization of this Thesis --- p.4 / Chapter 2 --- Previous Work --- p.5 / Chapter 3 --- Structure Recovery from Stereo-Motion Images --- p.7 / Chapter 3.1 --- Motion Model --- p.8 / Chapter 3.2 --- Stereo-Motion Model --- p.10 / Chapter 3.3 --- Inferring Stereo Correspondences --- p.13 / Chapter 3.4 --- Determining 3D Structure from One Stereo Pair --- p.17 / Chapter 3.5 --- Computational Complexity of Inference Process --- p.18 / Chapter 4 --- Experimental Results --- p.19 / Chapter 4.1 --- Synthetic Images and Statistical Results --- p.19 / Chapter 4.2 --- Real Image Sequences --- p.21 / Chapter 4.2.1 --- House Model' Image Sequences --- p.22 / Chapter 4.2.2 --- Oscilloscope and Soda Can' Image Sequences --- p.23 / Chapter 4.2.3 --- Bowl' Image Sequences --- p.24 / Chapter 4.2.4 --- Building' Image Sequences --- p.27 / Chapter 4.3 --- Computational Time of Experiments --- p.28 / Chapter 5 --- Determining Motion and Structure from All Stereo Pairs --- p.30 / Chapter 5.1 --- Determining Motion and Structure --- p.31 / Chapter 5.2 --- Identifying Incorrect Motion Correspondences --- p.33 / Chapter 6 --- More Experiments --- p.34 / Chapter 6.1 --- Synthetic Cube' Images --- p.34 / Chapter 6.2 --- Snack Bag´ة Image Sequences --- p.35 / Chapter 6.3 --- Comparison with Structure Recovered from One Stereo Pair --- p.37 / Chapter 7 --- Conclusion --- p.41 / Chapter A --- Basic Concepts in Computer Vision --- p.43 / Chapter A.1 --- Camera Projection Model --- p.43 / Chapter A.2 --- Epipolar Constraint in Stereo Vision --- p.47 / Chapter B --- Inferring Stereo Correspondences with Matrices of Rank < 4 --- p.49 / Chapter C --- Generating Image Reprojection --- p.51 / Chapter D --- Singular Value Decomposition --- p.53 / Chapter E --- Quaternion --- p.55