Ng, Cheuk Hang. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 89-95). / Abstracts in English and Chinese. / Abstract --- p.ii / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Problem Definition --- p.2 / Chapter 1.2 --- Main Contributions --- p.4 / Chapter 1.3 --- Thesis Organization --- p.5 / Chapter 2 --- Background --- p.6 / Chapter 2.1 --- Background of Peer-to-Peer --- p.6 / Chapter 2.2 --- Background of Content-Based Image Retrieval System --- p.9 / Chapter 2.3 --- Literature Review of Peer-to-Peer Application --- p.10 / Chapter 2.4 --- Literature Review of Discovery Mechanisms for Peer-to-Peer Applications --- p.13 / Chapter 2.4.1 --- Centralized Search --- p.13 / Chapter 2.4.2 --- Distributed Search - Flooding --- p.15 / Chapter 2.4.3 --- Distributed Search - Distributed Hash Table --- p.21 / Chapter 3 --- Peer Clustering and Firework Query Model --- p.25 / Chapter 3.1 --- Peer Clustering --- p.26 / Chapter 3.1.1 --- Peer Clustering - Simplified Version --- p.27 / Chapter 3.1.2 --- Peer Clustering - Single Cluster Version --- p.29 / Chapter 3.1.3 --- "Peer Clustering - Single Cluster, Multiple Layers of Con- nection Version" --- p.34 / Chapter 3.1.4 --- Peer Clustering - Multiple Clusters Version --- p.35 / Chapter 3.2 --- Firework Query Model Over Clustered Network --- p.38 / Chapter 4 --- Experiments and Results --- p.43 / Chapter 4.1 --- Simulation Model of Peer-to-Peer Network --- p.43 / Chapter 4.2 --- Performance Metrics --- p.45 / Chapter 4.3 --- Experiment Results --- p.47 / Chapter 4.3.1 --- Performances in different Number of Peers in P2P Network --- p.47 / Chapter 4.3.2 --- Performances in different TTL value of query packet in P2P Network --- p.52 / Chapter 4.3.3 --- "Performances in different different data sets, synthetic data and real data" --- p.55 / Chapter 4.3.4 --- Performances in different number of local clusters of each peer in P2P Network --- p.58 / Chapter 4.4 --- Evaluation of different clustering algorithms --- p.64 / Chapter 5 --- Distributed COntent-based Visual Information Retrieval (DIS- COVIR) --- p.67 / Chapter 5.1 --- Architecture of DISCOVIR and Functionality of DISCOVIR Components --- p.68 / Chapter 5.2 --- Flow of Operations --- p.72 / Chapter 5.2.1 --- Preprocessing (1) --- p.73 / Chapter 5.2.2 --- Connection Establishment (2) --- p.75 / Chapter 5.2.3 --- "Query Message Routing (3,4,5)" --- p.75 / Chapter 5.2.4 --- "Query Result Display (6,7)" --- p.78 / Chapter 5.3 --- Gnutella Message Modification --- p.78 / Chapter 5.4 --- DISCOVIR EVERYWHERE --- p.81 / Chapter 5.4.1 --- Design Goal of DISCOVIR Everywhere --- p.82 / Chapter 5.4.2 --- Architecture and System Components of DISCOVIR Ev- erywhere --- p.83 / Chapter 5.4.3 --- Flow of Operations --- p.84 / Chapter 5.4.4 --- Advantages of DISCOVIR Everywhere over Prevalent Web-based Search Engine --- p.86 / Chapter 6 --- Conclusion --- p.87 / Bibliography --- p.89

Lee Keung Tat. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 81-86). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgments --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation --- p.1 / Chapter 1.2 --- Contribution --- p.3 / Chapter 1.3 --- Previous Work --- p.5 / Chapter 1.4 --- Thesis Organization --- p.9 / Chapter 2 --- Overview --- p.10 / Chapter 3 --- Data Acquisition --- p.14 / Chapter 3.1 --- Acquiring the Surface Model --- p.14 / Chapter 3.2 --- Camera Calibration --- p.16 / Chapter 3.3 --- Capturing Image with Camera Pose --- p.18 / Chapter 3.3.1 --- Fastrack --- p.19 / Chapter 3.3.2 --- Tracking the Camera Pose --- p.21 / Chapter 3.3.3 --- Calibrating the Tracking System --- p.23 / Chapter 3.4 --- Summary --- p.32 / Chapter 4 --- Data Fusion --- p.33 / Chapter 4.1 --- Converting Surface Model to Point-Based Model --- p.33 / Chapter 4.2 --- Registering the Radiance Values onto the Point-Based Model --- p.36 / Chapter 4.3 --- Scattered Data Fitting --- p.40 / Chapter 4.3.1 --- Spherical Delaunay Triangulation --- p.41 / Chapter 4.3.2 --- Hierarchical Spherical Triangulation --- p.46 / Chapter 4.3.3 --- Interpolation --- p.49 / Chapter 4.4 --- Data Compression --- p.50 / Chapter 4.5 --- Summary --- p.52 / Chapter 5 --- Multiresolution Point-Based Representation and Rendering --- p.53 / Chapter 5.1 --- Multiresolution Point-Based Representation --- p.55 / Chapter 5.1.1 --- Construction --- p.57 / Chapter 5.2 --- Rendering --- p.62 / Chapter 5.2.1 --- Culling --- p.63 / Chapter 5.2.2 --- Drawing the Node --- p.66 / Chapter 5.3 --- Summary --- p.68 / Chapter 6 --- Experimental Results --- p.69 / Chapter 6.1 --- Tested Objects --- p.69 / Chapter 6.2 --- Evaluation --- p.70 / Chapter 6.3 --- Summary --- p.78 / Chapter 7 --- Conclusion --- p.79 / Chapter 7.1 --- Summary --- p.79 / Chapter 7.2 --- Future Direction --- p.80 / Bibliography --- p.81

Sia Ka Cheung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 85-91). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Problem Statement --- p.1 / Chapter 1.2 --- Contributions --- p.3 / Chapter 1.3 --- Thesis Organization --- p.4 / Chapter 2 --- Background --- p.5 / Chapter 2.1 --- Content-Based Image Retrieval --- p.5 / Chapter 2.1.1 --- Feature Extraction --- p.6 / Chapter 2.1.2 --- Indexing and Retrieval --- p.7 / Chapter 2.2 --- Relevance Feedback --- p.7 / Chapter 2.2.1 --- Weight Updating --- p.9 / Chapter 2.2.2 --- Bayesian Formulation --- p.11 / Chapter 2.2.3 --- Statistical Approaches --- p.12 / Chapter 2.2.4 --- Inter-query Feedback --- p.12 / Chapter 2.3 --- Peer-to-Peer Information Retrieval --- p.14 / Chapter 2.3.1 --- Distributed Hash Table Techniques --- p.16 / Chapter 2.3.2 --- Routing Indices and Shortcuts --- p.17 / Chapter 2.3.3 --- Content-Based Retrieval in P2P Systems --- p.18 / Chapter 3 --- Parameter Estimation-Based Relevance Feedback --- p.21 / Chapter 3.1 --- Parameter Estimation of Target Distribution --- p.21 / Chapter 3.1.1 --- Motivation --- p.21 / Chapter 3.1.2 --- Model --- p.23 / Chapter 3.1.3 --- Relevance Feedback --- p.24 / Chapter 3.1.4 --- Maximum Entropy Display --- p.26 / Chapter 3.2 --- Self-Organizing Map Based Inter-Query Feedback --- p.27 / Chapter 3.2.1 --- Motivation --- p.27 / Chapter 3.2.2 --- Initialization and Replication of SOM --- p.29 / Chapter 3.2.3 --- SOM Training for Inter-query Feedback --- p.31 / Chapter 3.2.4 --- Target Estimation and Display Set Selection for Intra- query Feedback --- p.33 / Chapter 3.3 --- Experiment --- p.35 / Chapter 3.3.1 --- Study of Parameter Estimation Method Using Synthetic Data --- p.35 / Chapter 3.3.2 --- Performance Study in Intra- and Inter- Query Feedback . --- p.40 / Chapter 3.4 --- Conclusion --- p.42 / Chapter 4 --- Distributed COntent-based Visual Information Retrieval --- p.44 / Chapter 4.1 --- Introduction --- p.44 / Chapter 4.2 --- Peer Clustering --- p.45 / Chapter 4.2.1 --- Basic Version --- p.45 / Chapter 4.2.2 --- Single Cluster Version --- p.47 / Chapter 4.2.3 --- Multiple Clusters Version --- p.51 / Chapter 4.3 --- Firework Query Model --- p.53 / Chapter 4.4 --- Implementation and System Architecture --- p.57 / Chapter 4.4.1 --- Gnutella Message Modification --- p.57 / Chapter 4.4.2 --- Architecture of DISCOVIR --- p.59 / Chapter 4.4.3 --- Flow of Operations --- p.60 / Chapter 4.5 --- Experiments --- p.62 / Chapter 4.5.1 --- Simulation Model of the Peer-to-Peer Network --- p.62 / Chapter 4.5.2 --- Number of Peers --- p.66 / Chapter 4.5.3 --- TTL of Query Message --- p.70 / Chapter 4.5.4 --- Effects of Data Resolution on Query Efficiency --- p.73 / Chapter 4.5.5 --- Discussion --- p.74 / Chapter 4.6 --- Conclusion --- p.77 / Chapter 5 --- Future Works and Conclusion --- p.79 / Chapter A --- Derivation of Update Equation --- p.81 / Chapter B --- An Efficient Discovery of Signatures --- p.82 / Bibliography --- p.85

Yip King-Fung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 84-89). / Abstracts in English and Chinese. / Abstract --- p.i / 論文摘要 --- p.iii / Table of Contents --- p.iv / List of Abbreviations --- p.vi / Acknowledgements --- p.vii / Chapter 1. --- Introduction --- p.1 / Chapter 1.1. --- Background --- p.1 / Chapter 1.2. --- Motivation --- p.3 / Chapter 1.3. --- Thesis Organization --- p.4 / Chapter 2. --- A Survey of Content-based Image Retrieval --- p.5 / Chapter 2.1. --- Text-based Image Retrieval --- p.5 / Chapter 2.2. --- Content-Based Image Retrieval --- p.7 / Chapter 2.2.1. --- Content-Based Image Retrieval Systems --- p.7 / Chapter 2.2.2. --- Query Methods --- p.9 / Chapter 2.2.3. --- Image Features --- p.11 / Chapter 2.2.4. --- Summary --- p.16 / Chapter 3. --- Visual Thesaurus using SOM --- p.17 / Chapter 3.1. --- Algorithm --- p.17 / Chapter 3.1.1. --- Image Representation --- p.17 / Chapter 3.1.2. --- Self-Organizing Map --- p.21 / Chapter 3.2. --- Preliminary Experiment --- p.27 / Chapter 3.2.1. --- Feature differences --- p.27 / Chapter 3.2.2. --- Labeling differences --- p.30 / Chapter 4. --- Experiment --- p.33 / Chapter 4.1. --- Subjects --- p.33 / Chapter 4.2. --- Apparatus --- p.33 / Chapter 4.2.1. --- Systems --- p.33 / Chapter 4.2.2. --- Test Databases --- p.33 / Chapter 4.3. --- Procedure --- p.34 / Chapter 4.3.1. --- Description --- p.35 / Chapter 4.3.2. --- SOM (text) --- p.36 / Chapter 4.3.3. --- SOM (image) --- p.38 / Chapter 4.3.4. --- QBE (text) --- p.40 / Chapter 4.3.5. --- QBE (image) --- p.42 / Chapter 4.3.6. --- Questionnaire --- p.44 / Chapter 4.3.7. --- Experiment Flow --- p.45 / Chapter 4.4. --- Results --- p.46 / Chapter 4.5. --- Discussion --- p.51 / Chapter 5. --- Quantizing Color Histogram --- p.55 / Chapter 5.1. --- Algorithm --- p.56 / Chapter 5.1.1. --- Codebook Generation Phrase --- p.57 / Chapter 5.1.2. --- Histogram Generation Phrase --- p.66 / Chapter 5.2. --- Experiment --- p.67 / Chapter 5.2.1. --- Test Database --- p.67 / Chapter 5.2.2. --- Evaluation Methods --- p.67 / Chapter 5.2.3. --- Results and Discussion --- p.69 / Chapter 5.2.4. --- Summary --- p.74 / Chapter 6. --- Relevance Feedback --- p.75 / Chapter 6.1. --- Relevance Feedback in Text Information Retrieval --- p.75 / Chapter 6.2. --- Relevance Feedback in Multimedia Information Retrieval --- p.76 / Chapter 6.3. --- Relevance Feedback in Visual Thesaurus --- p.76 / Chapter 7. --- Conclusions --- p.80 / Chapter 7.1. --- Applications --- p.81 / Chapter 7.2. --- Future Directions --- p.81 / Chapter 7.2.1. --- SOM Generation --- p.81 / Chapter 7.2.2. --- Hybrid Architecture --- p.82 / References --- p.84

Firstly, the characteristics of HD videos are studied quantitatively. The results show that HD videos distinguish from other lower resolution videos by higher spatial correlation and special power spectral density (PSD), mainly distributed along the vertical and horizontal directions. / Secondly, two techniques for HD video coding are developed based on the aforementioned analysis results. To exploit the spatial property, 2D order-16 transforms are proposed to code the higher correlated signals more efficiently. Specially, two series of 2D order-16 integer transforms, named modified integer cosine transform (MICT) and non-orthogonal integer cosine transform (NICT), are studied and developed to provide different trade-offs between the performance and the complexity. Based on the property of special PSD, parametric interpolation filter (PIF) is proposed for motion-compensated prediction (MCP). Not only can PIF track the non-stationary statistics of video signals as the related work shows, but also it represents interpolation filters by parameters instead of individual coefficients, thus solving the conflict of the accuracy of coefficients and the size of side information. The experimental results show the proposed two coding techniques significantly outperform their equivalents in the state-of-the-art international video coding standards. / Thirdly, interlaced HD videos are studied, and to satisfy different delay constraints, two real-time de-interlacing algorithms are proposed specially for H.264 coded videos. They adapt to local activities, according to the syntax element (SE) values. Accuracy analysis is also introduced to deal with the disparity between the SE values and the real motions and textures. The de-interlacers provide better visual quality than the commonly used ones and can de-interlace 1080i sequences in real time on PCs. / Today, High-Definition (HD) videos become more and more popular with many applications. This thesis analyzes the characteristics of HD videos and develops the appropriate coding and processing techniques accordingly for hybrid video coding. / Dong, Jie. / Adviser: King Ngi Ngan. / Source: Dissertation Abstracts International, Volume: 72-01, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 153-158). / 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 Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

Leung, Man Chuen. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves 81-88). / Abstract also in Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation and Objective --- p.1 / Chapter 1.2 --- Contribution --- p.3 / Chapter 1.3 --- Organization of the Thesis --- p.4 / Chapter 2 --- Background --- p.5 / Chapter 2.1 --- Introduction --- p.5 / Chapter 2.2 --- Static Projector and Screen Systems --- p.6 / Chapter 2.3 --- Dynamic Projector or Screen Systems --- p.9 / Chapter 2.3.1 --- Movable Projector Systems --- p.10 / Chapter 2.3.2 --- Dynamic Screen Systems --- p.11 / Chapter 2.4 --- Summary --- p.17 / Chapter 3 --- System Overview --- p.18 / Chapter 3.1 --- System Design --- p.18 / Chapter 3.2 --- Our Approach --- p.18 / Chapter 3.2.1 --- Offline Projector Camera Calibration --- p.20 / Chapter 3.2.2 --- Quadrangle Detection and Tracking --- p.20 / Chapter 3.2.3 --- Projection --- p.22 / Chapter 3.3 --- Extension --- p.22 / Chapter 4 --- Projector-Camera Pair Calibration --- p.23 / Chapter 4.1 --- Introduction --- p.23 / Chapter 4.2 --- Projective Geometry of a Projector --- p.25 / Chapter 4.3 --- Calibration Method --- p.27 / Chapter 5 --- Quadrangle Detection and Tracking --- p.31 / Chapter 5.1 --- Introduction --- p.31 / Chapter 5.2 --- Line Feature Extraction --- p.33 / Chapter 5.3 --- Automatic Quadrangle Detection --- p.33 / Chapter 5.4 --- Real-time Quadrangle Tracking --- p.36 / Chapter 5.4.1 --- State Dynamic Model --- p.39 / Chapter 5.4.2 --- Observation Model --- p.39 / Chapter 5.5 --- Tracking Lose Strategy --- p.41 / Chapter 5.5.1 --- Determination of Tracking Failure --- p.42 / Chapter 5.6 --- Recover from Tracking Failure --- p.43 / Chapter 6 --- Projection onto the Cardboard --- p.44 / Chapter 7 --- Implementation and Experiment Results --- p.47 / Chapter 7.1 --- Introduction --- p.47 / Chapter 7.2 --- Projector-Camera Pair Calibration --- p.49 / Chapter 7.3 --- Quadrangle Detection and Tracking --- p.51 / Chapter 7.3.1 --- Experiment 1 - Tracking precision and robustness against occlusion --- p.51 / Chapter 7.3.2 --- Experiment 2 - Robustness against dense clutter --- p.52 / Chapter 7.3.3 --- Experiment 3 - Tracking of a paper with printed content --- p.53 / Chapter 7.3.4 --- Experiment 4 - Moving camera --- p.53 / Chapter 7.3.5 --- Processing Time --- p.55 / Chapter 7.4 --- Projection Performance --- p.57 / Chapter 7.4.1 --- Projection Precision --- p.57 / Chapter 7.4.2 --- Projection Latency --- p.58 / Chapter 8 --- Limitations and Discussions --- p.61 / Chapter 8.1 --- Limitation on Projection Resolution --- p.61 / Chapter 8.2 --- Limitation on Depth of Field --- p.62 / Chapter 8.3 --- Tracking Stability and Processing Time --- p.62 / Chapter 8.4 --- Handling Projected Light --- p.63 / Chapter 8.5 --- Possible Extensions --- p.63 / Chapter 9 --- View Dependent Projection and Application --- p.65 / Chapter 9.1 --- View Dependent Projection --- p.65 / Chapter 9.2 --- Head Pose Tracking --- p.67 / Chapter 9.3 --- Application - Hand-held 3D Model Viewer --- p.68 / Chapter 9.3.1 --- Introduction --- p.68 / Chapter 9.3.2 --- Implementation Detail --- p.69 / Chapter 9.3.3 --- Experiment Results --- p.73 / Chapter 9.3.4 --- Discussions --- p.73 / Chapter 9.4 --- Summary --- p.75 / Chapter 10 --- Conclusions --- p.77 / A Pose Estimation of Cardboard --- p.79 / Bibliography --- p.81

Du, Hao. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (p. 61). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- 3D Reconstruction from 2D Line Drawings and its Applications --- p.1 / Chapter 1.2 --- Algorithmic Development of 3D Reconstruction from 2D Line Drawings --- p.3 / Chapter 1.2.1 --- Line Labeling and Realization Problem --- p.4 / Chapter 1.2.2 --- 3D Reconstruction from Multiple Line Drawings --- p.5 / Chapter 1.2.3 --- 3D Reconstruction from a Single Line Drawing --- p.6 / Chapter 1.3 --- Research Problems and Our Contributions --- p.12 / Chapter 2 --- Adaptive Parameter Setting --- p.15 / Chapter 2.1 --- Regularities in Optimization-Based 3D Reconstruction --- p.15 / Chapter 2.1.1 --- Face Planarity --- p.18 / Chapter 2.1.2 --- Line Parallelism --- p.19 / Chapter 2.1.3 --- Line Verticality --- p.19 / Chapter 2.1.4 --- Isometry --- p.19 / Chapter 2.1.5 --- Corner Orthogonality --- p.20 / Chapter 2.1.6 --- Skewed Facial Orthogonality --- p.21 / Chapter 2.1.7 --- Skewed Facial Symmetry --- p.22 / Chapter 2.1.8 --- Line Orthogonality --- p.24 / Chapter 2.1.9 --- Minimum Standard Deviation of Angles --- p.24 / Chapter 2.1.10 --- Face Perpendicularity --- p.24 / Chapter 2.1.11 --- Line Collinearity --- p.25 / Chapter 2.1.12 --- Whole Symmetry --- p.25 / Chapter 2.2 --- Adaptive Parameter Setting in the Objective Function --- p.26 / Chapter 2.2.1 --- Hill-Climbing Optimization Technique --- p.28 / Chapter 2.2.2 --- Adaptive Weight Setting and its Explanations --- p.29 / Chapter 3 --- Parameter Learning --- p.33 / Chapter 3.1 --- Construction of A Large 3D Object Database --- p.33 / Chapter 3.2 --- Training Dataset Generation --- p.34 / Chapter 3.3 --- Parameter Learning Framework --- p.37 / Chapter 3.3.1 --- Evolutionary Algorithms --- p.38 / Chapter 3.3.2 --- Reconstruction Error Calculation --- p.39 / Chapter 3.3.3 --- Parameter Learning Algorithm --- p.41 / Chapter 4 --- Experimental Results --- p.45 / Chapter 4.1 --- Adaptive Parameter Setting --- p.45 / Chapter 4.1.1 --- Use Manually-Set Weights --- p.45 / Chapter 4.1.2 --- Learn the Best Weights with Different Strategies --- p.48 / Chapter 4.2 --- Evolutionary-Algorithm-Based Parameter Learning --- p.49 / Chapter 5 --- Conclusions and Future Work --- p.53 / Bibliography --- p.55

Li, Sai Man. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 91-96). / Abstracts in English and Chinese. / Abstract --- p.2 / List of Figures --- p.6 / Acknowledgement --- p.10 / Chapter Chapter 1 --- Introduction --- p.11 / Chapter 1.1 --- Problem definition --- p.11 / Chapter 1.2. --- Proposed algorithm --- p.12 / Chapter 1.3. --- Main features --- p.14 / Chapter Chapter 2 --- Literature Review --- p.16 / Chapter 2.1 --- Local Feature Matching techniques --- p.16 / Chapter 2.2. --- Global Iterative alignment techniques --- p.19 / Chapter 2.3 --- Other Approaches --- p.20 / Chapter Chapter 3 --- Correspondence Matching --- p.21 / Chapter 3.1 --- Fundamental Techniques --- p.24 / Chapter 3.1.1 --- Geodesic Distance Approximation --- p.24 / Chapter 3.1.1.1 --- Dijkstra ´ةs algorithm --- p.25 / Chapter 3.1.1.2 --- Wavefront Propagation --- p.26 / Chapter 3.1.2 --- Farthest Point Sampling --- p.27 / Chapter 3.1.3 --- Curvature Estimation --- p.29 / Chapter 3.1.4 --- Radial Basis Function (RBF) --- p.32 / Chapter 3.1.5 --- Multi-dimensional Scaling (MDS) --- p.35 / Chapter 3.1.5.1 --- Classical MDS --- p.35 / Chapter 3.1.5.2 --- Fast MDS --- p.38 / Chapter 3.2 --- Matching Processes --- p.40 / Chapter 3.2.1 --- Posture Alignment --- p.42 / Chapter 3.2.1.1 --- Sign Flip Correction --- p.43 / Chapter 3.2.1.2 --- Input model Alignment --- p.49 / Chapter 3.2.2 --- Surface Fitting --- p.52 / Chapter 3.2.2.1 --- Optimizing Surface Fitness --- p.54 / Chapter 3.2.2.2 --- Optimizing Surface Smoothness --- p.56 / Chapter 3.2.3 --- Feature Matching Refinement --- p.59 / Chapter 3.2.3.1 --- Feature descriptor --- p.61 / Chapter 3.2.3.3 --- Feature Descriptor matching --- p.63 / Chapter Chapter 4 --- Experimental Result --- p.66 / Chapter 4.1 --- Result of the Fundamental Techniques --- p.66 / Chapter 4.1.1 --- Geodesic Distance Approximation --- p.67 / Chapter 4.1.2 --- Farthest Point Sampling (FPS) --- p.67 / Chapter 4.1.3 --- Radial Basis Function (RBF) --- p.69 / Chapter 4.1.4 --- Curvature Estimation --- p.70 / Chapter 4.1.5 --- Multi-Dimensional Scaling (MDS) --- p.71 / Chapter 4.2 --- Result of the Core Matching Processes --- p.73 / Chapter 4.2.1 --- Posture Alignment Step --- p.73 / Chapter 4.2.2 --- Surface Fitting Step --- p.78 / Chapter 4.2.3 --- Feature Matching Refinement --- p.82 / Chapter 4.2.4 --- Application of the proposed algorithm --- p.84 / Chapter 4.2.4.1 --- Design Automation in Garment Industry --- p.84 / Chapter 4.3 --- Analysis --- p.86 / Chapter 4.3.1 --- Performance --- p.86 / Chapter 4.3.2 --- Accuracy --- p.87 / Chapter 4.3.3 --- Approach Comparison --- p.88 / Chapter Chapter 5 --- Conclusion --- p.89 / Chapter 5.1 --- Strength and contributions --- p.89 / Chapter 5.2 --- Limitation and future works --- p.90 / References --- p.91

Pang, Wenjun. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves 83-88). / Abstracts in English and Chinese. / ACKNOWLEDGEMENTS --- p.ii / ABSTRACT --- p.iv / 摘要 --- p.v / CONTENTS --- p.vi / List of Tables --- p.viii / List of Figures --- p.ix / Chapter 1. --- INTRODUCTION --- p.1 / Chapter 1.1 --- Recent research work --- p.4 / Chapter 1.2 --- Objectives --- p.8 / Chapter 1.3 --- Thesis Organization --- p.10 / Chapter 2. --- FRACTAL MODELING --- p.12 / Chapter 2.1 --- Fractal and Fractal Art --- p.12 / Chapter 2.2 --- Fractal Geometry --- p.15 / Chapter 2.3 --- Construction of Fractals --- p.21 / Chapter 2.4 --- Fractal Measurement and Aesthetics --- p.27 / Chapter 3. --- OVERVIEW OF EVOLUTIONARY DESIGN --- p.30 / Chapter 3.1 --- Initialization --- p.33 / Chapter 3.2 --- Selection --- p.33 / Chapter 3.3 --- Reproduction --- p.34 / Chapter 3.4 --- Termination --- p.36 / Chapter 4. --- EVOLUTIONARY 3D FRACTAL MODELING --- p.38 / Chapter 4.1 --- Fractal Construction --- p.38 / Chapter 4.1.1 --- Self-similar Condition of Fractal --- p.38 / Chapter 4.1.2 --- Fractal Transformation (FT) IFS Formulation --- p.39 / Chapter 4.1.3 --- IFS Genotype and Phenotype Expression --- p.41 / Chapter 4.2 --- Evolutionary Algorithm --- p.43 / Chapter 4.2.1 --- Single-point Crossover --- p.45 / Chapter 4.2.2 --- Arithmetic Gaussian mutation --- p.45 / Chapter 4.2.3 --- Inferior Elimination --- p.46 / Chapter 4.3 --- Interactive Fine-tuning using FT IFS --- p.46 / Chapter 4.4 --- Gaussian Fitness Function --- p.48 / Chapter 5. --- GAUSSIAN AESTHETIC FITNESS FUNCTION --- p.49 / Chapter 5.1 --- Fitness Considerations --- p.50 / Chapter 5.2 --- Fitness Function Formulation --- p.53 / Chapter 5.3 --- Results and Discussion on Fitness Function --- p.55 / Chapter 6. --- EXPERIMENT RESULTS and DISCUSSION --- p.59 / Chapter 6.1 --- Experiment of Evolutionary Generation --- p.59 / Chapter 6.2 --- Comparison on Different Methods --- p.60 / Chapter 7. --- 3D FRACTALS RENDERING and APPLICATION --- p.62 / Chapter 7.1 --- Transforming Property and User Modification --- p.62 / Chapter 7.2 --- Visualization and Rendering of 3D Fractals --- p.66 / Chapter 7.3 --- Applications in Design --- p.74 / Chapter 8. --- CONCLUSIONS and FUTURE WORK --- p.81 / Chapter 8.1 --- Conclusions --- p.81 / Chapter 8.2 --- Future Work --- p.81 / BIBLIOGRAPHY --- p.83 / Appendix --- p.89 / Marching Cubes Method --- p.89

Chow, Yuk Pui. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 83-87). / Abstracts in English and Chinese. / Chapter 1. --- Introduction --- p.13-16 / Chapter 1.1. --- Motivation --- p.13 / Chapter 1.2 --- Objectives --- p.14-15 / Chapter 1.3 --- Thesis Organization --- p.16 / Chapter 2. --- Related Works --- p.17-24 / Chapter 2.1 --- Axial and the Free Form Deformation --- p.17 / Chapter 2.1.1 --- The Free-Form Deformation --- p.18 / Chapter 2.1.2 --- The Lattice-based Representation --- p.18 / Chapter 2.1.3 --- The Axial Deformation --- p.19-20 / Chapter 2.1.4 --- Curve Pair-based Representation --- p.21-22 / Chapter 2.2 --- Self Intersection Detection --- p.23-24 / Chapter 3. --- Axial Deformation with Controllable LCFs --- p.25-46 / Chapter 3.1 --- Related Methods --- p.25 / Chapter 3.2 --- Axial Space --- p.26-27 / Chapter 3.3 --- Definition of Local Coordinate Frame --- p.28-29 / Chapter 3.4 --- Constructing Axial Curve with LCFs --- p.30 / Chapter 3.5 --- Point Projection Method --- p.31-32 / Chapter 3.5.1 --- Optimum Reference Axial Curve Point --- p.33 / Chapter 3.6 --- Advantages using LCFs in Axial Deformation --- p.34 / Chapter 3.6.1 --- Deformation with Smooth Interpolated LCFs --- p.34-37 / Chapter 3.6.2 --- Used in Closed-curve Deformation --- p.38-39 / Chapter 3.6.3 --- Hierarchy of Axial Curve --- p.40 / Chapter 3.6.4 --- Applications in Soft Object Deformation --- p.41 / Chapter 3.7 --- Experiments and Results --- p.42-46 / Chapter 4. --- Self Intersection Detection of Axial Curve with LCFs --- p.47-76 / Chapter 4.1 --- Related Works --- p.48-49 / Chapter 4.2 --- Algorithms for Solving Self-intersection Problem with a set of LCFs --- p.50-51 / Chapter 4.2.1 --- The Intersection of Two Plane --- p.52 / Chapter 4.2.1.1 --- Constructing the Normal Plane --- p.53-54 / Chapter 4.2.1.2 --- A Line Formed by Two Planes Intersection --- p.55-57 / Chapter 4.2.1.3 --- Problems --- p.58 / Chapter 4.2.1.4 --- Sphere as Constraint --- p.59-60 / Chapter 4.2.1.5 --- Intersecting Line between Two Circular Discs --- p.61 / Chapter 4.2.2 --- Distance between a Mesh Vertex and a Curve Point --- p.62-63 / Chapter 4.2.2.1 --- Possible Cases of a Line and a Circle --- p.64-66 / Chapter 4.3 --- Definition Proof --- p.67 / Chapter 4.3.1 --- Define the Meaning of Self-intersection --- p.67 / Chapter 4.3.2 --- Cross Product of Two Vectors --- p.68 / Chapter 4.4 --- Factors Affecting the Accuracy of the Algorithm --- p.69 / Chapter 4.3.1 --- High Curvature of the Axial Curve --- p.69-70 / Chapter 4.3.2 --- Mesh Density of an Object. --- p.71-73 / Chapter 4.5 --- Architecture of the Self Intersection Algorithm --- p.74 / Chapter 4.6 --- Experimental Results --- p.75- 79 / Chapter 5. --- Conclusions and Future Development --- p.80-82 / Chapter 5.1 --- Contribution and Conclusions --- p.80-81 / Chapter 5.2 --- Limitations and Future Developments --- p.82 / References --- p.83-87