by Yingli Tian. / Thesis (Ph.D.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 202-222). / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Physics-Based Shape Recovery Techniques --- p.3 / Chapter 1.2 --- Proposed Approaches to Shape Recovery in this Thesis --- p.9 / Chapter 1.3 --- Thesis Outline --- p.13 / Chapter 2 --- Camera Model in Color Vision --- p.15 / Chapter 2.1 --- Introduction --- p.15 / Chapter 2.2 --- Spectral Linearization --- p.17 / Chapter 2.3 --- Image Balancing --- p.21 / Chapter 2.4 --- Spectral Sensitivity --- p.24 / Chapter 2.5 --- Color Clipping and Blooming --- p.24 / Chapter 3 --- Extended Light Source Models --- p.27 / Chapter 3.1 --- Introduction --- p.27 / Chapter 3.2 --- A Spherical Light Model in 2D Coordinate System --- p.30 / Chapter 3.2.1 --- Basic Photometric Function for Hybrid Surfaces under a Point Light Source --- p.32 / Chapter 3.2.2 --- Photometric Function for Hybrid Surfaces under the Spher- ical Light Source --- p.34 / Chapter 3.3 --- A Spherical Light Model in 3D Coordinate System --- p.36 / Chapter 3.3.1 --- Radiance of the Spherical Light Source --- p.36 / Chapter 3.3.2 --- Surface Brightness Illuminated by One Point of the Spher- ical Light Source --- p.38 / Chapter 3.3.3 --- Surface Brightness Illuminated by the Spherical Light Source --- p.39 / Chapter 3.3.4 --- Rotating the Source-Object Coordinate to the Camera- Object Coordinate --- p.41 / Chapter 3.3.5 --- Surface Reflection Model --- p.44 / Chapter 3.4 --- Rectangular Light Model in 3D Coordinate System --- p.45 / Chapter 3.4.1 --- Radiance of a Rectangular Light Source --- p.45 / Chapter 3.4.2 --- Surface Brightness Illuminated by One Point of the Rect- angular Light Source --- p.47 / Chapter 3.4.3 --- Surface Brightness Illuminated by a Rectangular Light Source --- p.47 / Chapter 4 --- Shape Recovery from Specular Reflection --- p.54 / Chapter 4.1 --- Introduction --- p.54 / Chapter 4.2 --- Theory of the First Method --- p.57 / Chapter 4.2.1 --- Torrance-Sparrow Reflectance Model --- p.57 / Chapter 4.2.2 --- Relationship Between Surface Shapes from Different Images --- p.60 / Chapter 4.3 --- Theory of the Second Method --- p.65 / Chapter 4.3.1 --- Getting the Depth of a Reference Point --- p.65 / Chapter 4.3.2 --- Recovering the Depth and Normal of a Specular Point Near the Reference Point --- p.67 / Chapter 4.3.3 --- Recovering Local Shape of the Object by Specular Reflection --- p.69 / Chapter 4.4 --- Experimental Results and Discussions --- p.71 / Chapter 4.4.1 --- Experimental System and Results of the First Method --- p.71 / Chapter 4.4.2 --- Experimental System and Results of the Second Method --- p.76 / Chapter 5 --- Shape Recovery from One Sequence of Color Images --- p.81 / Chapter 5.1 --- Introduction --- p.81 / Chapter 5.2 --- Temporal-color Space Analysis of Reflection --- p.84 / Chapter 5.3 --- Estimation of Illuminant Color Ks --- p.88 / Chapter 5.4 --- Estimation of the Color Vector of the Body-reflection Component Kl --- p.89 / Chapter 5.5 --- Separating Specular and Body Reflection Components and Re- covering Surface Shape and Reflectance --- p.91 / Chapter 5.6 --- Experiment Results and Discussions --- p.92 / Chapter 5.6.1 --- Results with Interreflection --- p.93 / Chapter 5.6.2 --- Results Without Interreflection --- p.93 / Chapter 5.6.3 --- Simulation Results --- p.95 / Chapter 5.7 --- Analysis of Various Factors on the Accuracy --- p.96 / Chapter 5.7.1 --- Effects of Number of Samples --- p.96 / Chapter 5.7.2 --- Effects of Noise --- p.99 / Chapter 5.7.3 --- Effects of Object Size --- p.99 / Chapter 5.7.4 --- Camera Optical Axis Not in Light Source Plane --- p.102 / Chapter 5.7.5 --- Camera Optical Axis Not Passing Through Object Center --- p.105 / Chapter 6 --- Shape Recovery from Two Sequences of Images --- p.107 / Chapter 6.1 --- Introduction --- p.107 / Chapter 6.2 --- Method for 3D Shape Recovery from Two Sequences of Images --- p.109 / Chapter 6.3 --- Genetics-Based Method --- p.111 / Chapter 6.4 --- Experimental Results and Discussions --- p.115 / Chapter 6.4.1 --- Simulation Results --- p.115 / Chapter 6.4.2 --- Real Experimental Results --- p.118 / Chapter 7 --- Shape from Shading for Non-Lambertian Surfaces --- p.120 / Chapter 7.1 --- Introduction --- p.120 / Chapter 7.2 --- Reflectance Map for Non-Lambertian Color Surfaces --- p.123 / Chapter 7.3 --- Recovering Non-Lambertian Surface Shape from One Color Image --- p.127 / Chapter 7.3.1 --- Segmenting Hybrid Areas from Diffuse Areas Using Hue Information --- p.127 / Chapter 7.3.2 --- Calculating Intensities of Specular and Diffuse Compo- nents on Hybrid Areas --- p.128 / Chapter 7.3.3 --- Recovering Shape from Shading --- p.129 / Chapter 7.4 --- Experimental Results and Discussions --- p.131 / Chapter 7.4.1 --- Simulation Results --- p.131 / Chapter 7.4.2 --- Real Experimental Results --- p.136 / Chapter 8 --- Shape from Shading under Multiple Extended Light Sources --- p.142 / Chapter 8.1 --- Introduction --- p.142 / Chapter 8.2 --- Reflectance Map for Lambertian Surface Under Multiple Rectan- gular Light Sources --- p.144 / Chapter 8.3 --- Recovering Surface Shape Under Multiple Rectangular Light Sources --- p.148 / Chapter 8.4 --- Experimental Results and Discussions --- p.150 / Chapter 8.4.1 --- Synthetic Image Results --- p.150 / Chapter 8.4.2 --- Real Image Results --- p.152 / Chapter 9 --- Shape from Shading in Unknown Environments by Neural Net- works --- p.167 / Chapter 9.1 --- Introduction --- p.167 / Chapter 9.2 --- Shape Estimation --- p.169 / Chapter 9.2.1 --- Shape Recovery Problem under Multiple Rectangular Ex- tended Light Sources --- p.169 / Chapter 9.2.2 --- Forward Network Representation of Surface Normals --- p.170 / Chapter 9.2.3 --- Shape Estimation --- p.174 / Chapter 9.3 --- Application of the Neural Network in Shape Recovery --- p.174 / Chapter 9.3.1 --- Structure of the Neural Network --- p.174 / Chapter 9.3.2 --- Normalization of the Input and Output Patterns --- p.175 / Chapter 9.4 --- Experimental Results and Discussions --- p.178 / Chapter 9.4.1 --- Results for Lambertian Surface under One Rectangular Light --- p.178 / Chapter 9.4.2 --- Results for Lambertian Surface under Four Rectangular Light Sources --- p.180 / Chapter 9.4.3 --- Results for Hybrid Surface under One Rectangular Light Sources --- p.190 / Chapter 9.4.4 --- Discussions --- p.190 / Chapter 10 --- Summary and Conclusions --- p.191 / Chapter 10.1 --- Summary Results and Contributions --- p.192 / Chapter 10.2 --- Directions of Future Research --- p.199 / Bibliography --- p.202

Fu Chi-wing. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1999. / Includes bibliographical references (leaves 141-149). / Abstract --- p.i / Acknowledgments --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Introduction to Image-based Rendering --- p.1 / Chapter 1.2 --- Scene Complexity Independent Property --- p.2 / Chapter 1.3 --- Application of this Research Work --- p.3 / Chapter 1.4 --- Organization of this Thesis --- p.4 / Chapter 2 --- Illumination Control --- p.7 / Chapter 2.1 --- Introduction --- p.7 / Chapter 2.2 --- Apparent BRDF of Pixel --- p.8 / Chapter 2.3 --- Sampling Illumination Information --- p.11 / Chapter 2.4 --- Re-rendering --- p.13 / Chapter 2.4.1 --- Light Direction --- p.15 / Chapter 2.4.2 --- Light Intensity --- p.15 / Chapter 2.4.3 --- Multiple Light Sources --- p.15 / Chapter 2.4.4 --- Type of Light Sources --- p.18 / Chapter 2.5 --- Data Compression --- p.22 / Chapter 2.5.1 --- Intra-pixel coherence --- p.22 / Chapter 2.5.2 --- Inter-pixel coherence --- p.22 / Chapter 2.6 --- Implementation and Result --- p.22 / Chapter 2.6.1 --- An Interactive Viewer --- p.22 / Chapter 2.6.2 --- Lazy Re-rendering --- p.24 / Chapter 2.7 --- Conclusion --- p.24 / Chapter 3 --- Navigation Control - Triangle-based Warping Rule --- p.29 / Chapter 3.1 --- Introduction to Navigation Control --- p.29 / Chapter 3.2 --- Related Works --- p.30 / Chapter 3.3 --- Epipolar Geometry (Perspective Projection Manifold) --- p.31 / Chapter 3.4 --- Drawing Order for Pixel-Sized Entities --- p.35 / Chapter 3.5 --- Triangle-based Image Warping --- p.36 / Chapter 3.5.1 --- Image-based Triangulation --- p.36 / Chapter 3.5.2 --- Image-based Visibility Sorting --- p.40 / Chapter 3.5.3 --- Topological Sorting --- p.44 / Chapter 3.6 --- Results --- p.46 / Chapter 3.7 --- Conclusion --- p.48 / Chapter 4 --- Panoramic Projection Manifold --- p.52 / Chapter 4.1 --- Epipolar Geometry (Spherical Projection Manifold) --- p.53 / Chapter 4.2 --- Image Triangulation --- p.56 / Chapter 4.2.1 --- Optical Flow --- p.56 / Chapter 4.2.2 --- Image Gradient and Potential Function --- p.57 / Chapter 4.2.3 --- Triangulation --- p.58 / Chapter 4.3 --- Image-based Visibility Sorting --- p.58 / Chapter 4.3.1 --- Mapping Criteria --- p.58 / Chapter 4.3.2 --- Ordering of Two Triangles --- p.59 / Chapter 4.3.3 --- Graph Construction and Topological Sort --- p.63 / Chapter 4.4 --- Results --- p.63 / Chapter 4.5 --- Conclusion --- p.65 / Chapter 5 --- Panoramic-based Navigation using Real Photos --- p.69 / Chapter 5.1 --- Introduction --- p.69 / Chapter 5.2 --- System Overview --- p.71 / Chapter 5.3 --- Correspondence Matching --- p.72 / Chapter 5.3.1 --- Basic Model of Epipolar Geometry --- p.72 / Chapter 5.3.2 --- Epipolar Geometry between two Neighbor Panoramic Nodes --- p.73 / Chapter 5.3.3 --- Line and Patch Correspondence Matching --- p.74 / Chapter 5.4 --- Triangle-based Warping --- p.75 / Chapter 5.4.1 --- Why Warp Triangle --- p.75 / Chapter 5.4.2 --- Patch and Layer Construction --- p.76 / Chapter 5.4.3 --- Triangulation and Mesh Subdivision --- p.76 / Chapter 5.4.4 --- Layered Triangle-based Warping --- p.77 / Chapter 5.5 --- Implementation --- p.78 / Chapter 5.5.1 --- Image Sampler and Panoramic Stitcher --- p.78 / Chapter 5.5.2 --- Interactive Correspondence Matcher and Triangulation --- p.79 / Chapter 5.5.3 --- Basic Panoramic Viewer --- p.79 / Chapter 5.5.4 --- Formulating Drag Vector and vn --- p.80 / Chapter 5.5.5 --- Controlling Walkthrough Parameter --- p.82 / Chapter 5.5.6 --- Interactive Web-based Panoramic Viewer --- p.83 / Chapter 5.6 --- Results --- p.84 / Chapter 5.7 --- Conclusion and Possible Enhancements --- p.84 / Chapter 6 --- Compositing Warped Images for Object-based Viewing --- p.89 / Chapter 6.1 --- Modeling Object-based Viewing --- p.89 / Chapter 6.2 --- Triangulation and Convex Hull Criteria --- p.92 / Chapter 6.3 --- Warping Multiple Views --- p.94 / Chapter 6.3.1 --- Method I --- p.95 / Chapter 6.3.2 --- Method II --- p.95 / Chapter 6.3.3 --- Method III --- p.95 / Chapter 6.4 --- Results --- p.97 / Chapter 6.5 --- Conclusion --- p.100 / Chapter 7 --- Complete Rendering Pipeline --- p.107 / Chapter 7.1 --- Reviews on Illumination and Navigation --- p.107 / Chapter 7.1.1 --- Illumination Rendering Pipeline --- p.107 / Chapter 7.1.2 --- Navigation Rendering Pipeline --- p.108 / Chapter 7.2 --- Analysis of the Two Rendering Pipelines --- p.109 / Chapter 7.2.1 --- Combination on the Architectural Level --- p.109 / Chapter 7.2.2 --- Ensuring Physical Correctness --- p.111 / Chapter 7.3 --- Generalizing Apparent BRDF --- p.112 / Chapter 7.3.1 --- Difficulties to Encode BRDF with Spherical Harmonics --- p.112 / Chapter 7.3.2 --- Generalize Apparent BRDF --- p.112 / Chapter 7.3.3 --- Related works for Encoding the generalized apparent BRDF --- p.113 / Chapter 7.4 --- Conclusion --- p.116 / Chapter 8 --- Conclusion --- p.117 / Chapter A --- Spherical Harmonics --- p.120 / Chapter B --- It is Rare for Cycles to Exist in the Drawing Order Graph --- p.123 / Chapter B.1 --- Theorem 3 --- p.123 / Chapter B.2 --- Inside and Outside-directed Triangles in a Triangular Cycle --- p.125 / Chapter B.2.1 --- Assumption --- p.126 / Chapter B.2.2 --- Inside-directed and Outside-directed triangles --- p.126 / Chapter B.3 --- Four Possible Cases to Form a Cycle --- p.127 / Chapter B.3.1 --- Case(l) Triangular Fan --- p.128 / Chapter B.3.2 --- Case(2) Two Outside-directed Triangles --- p.129 / Chapter B.3.3 --- Case(3) Three Outside-directed Triangles --- p.130 / Chapter B.3.4 --- Case(4) More than Three Outside-directed Triangles --- p.131 / Chapter B.4 --- Experiment --- p.132 / Chapter C --- Deriving the Epipolar Line Formula on Cylindrical Projection Manifold --- p.133 / Chapter C.1 --- Notations --- p.133 / Chapter C.2 --- General Formula --- p.134 / Chapter C.3 --- Simplify the General Formula to a Sine Curve --- p.137 / Chapter C.4 --- Show that the Epipolar Line is a Sine Curve Segment --- p.139 / Chapter D --- Publications Related to this Research Work --- p.141 / Bibliography --- p.143

Lao Tze Kin Jackie. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 83-87). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- 3D Modeling using Active Contour --- p.3 / Chapter 1.2 --- Rectangular Virtual Environment Construction --- p.5 / Chapter 1.3 --- Thesis Contribution --- p.7 / Chapter 1.4 --- Thesis Outline --- p.7 / Chapter 2 --- Background --- p.9 / Chapter 2.1 --- Panoramic Representation --- p.9 / Chapter 2.1.1 --- Static Mosaic --- p.10 / Chapter 2.1.2 --- Advanced Mosaic Representation --- p.15 / Chapter 2.1.3 --- Panoramic Walkthrough --- p.17 / Chapter 2.2 --- Active Contour Model --- p.24 / Chapter 2.2.1 --- Parametric Active Contour Model --- p.28 / Chapter 2.3 --- 3D Shape Estimation --- p.29 / Chapter 2.3.1 --- Model Formation with both intrinsic and extrinsic parameters --- p.29 / Chapter 2.3.2 --- Model Formation with only Intrinsic Parameter and Epipo- lar Geometry --- p.32 / Chapter 3 --- 3D Object Modeling using Active Contour --- p.39 / Chapter 3.1 --- Point Acquisition Through Active Contour --- p.40 / Chapter 3.2 --- Object Segmentation and Panorama Generation --- p.43 / Chapter 3.2.1 --- Object Segmentation --- p.44 / Chapter 3.2.2 --- Panorama Construction --- p.44 / Chapter 3.3 --- 3D modeling and Texture Mapping --- p.45 / Chapter 3.3.1 --- Texture Mapping From Parameterization --- p.46 / Chapter 3.4 --- Experimental Results --- p.48 / Chapter 3.4.1 --- Experimental Error --- p.49 / Chapter 3.4.2 --- Comparison between Virtual 3D Model with Actual Model --- p.54 / Chapter 3.4.3 --- Comparison with Existing Techniques --- p.55 / Chapter 3.5 --- Discussion --- p.55 / Chapter 4 --- Rectangular Virtual Environment Construction --- p.57 / Chapter 4.1 --- Rectangular Environment Construction using Traditional (Hori- zontal) Panoramic Scenes --- p.58 / Chapter 4.1.1 --- Image Manipulation --- p.59 / Chapter 4.1.2 --- Panoramic Mosaic Creation --- p.59 / Chapter 4.1.3 --- Measurement of Panning Angles --- p.61 / Chapter 4.1.4 --- Estimate Side Ratio --- p.62 / Chapter 4.1.5 --- Wireframe Modeling and Cylindrical Projection --- p.63 / Chapter 4.1.6 --- Experimental Results --- p.66 / Chapter 4.2 --- Rectangular Environment Construction using Vertical Panoramic Scenes --- p.67 / Chapter 4.3 --- Building virtual environments for complex scenes --- p.73 / Chapter 4.4 --- Comparison with Existing Techniques --- p.75 / Chapter 4.5 --- Discussion and Future Directions --- p.77 / Chapter 5 --- System Integration --- p.79 / Chapter 6 --- Conclusion --- p.81 / Bibliography --- p.87

by Ping-Fu Fung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1998. / Includes bibliographical references (leaves 98-102). / Abstract also in Chinese. / Abstract --- p.iv / Acknowledgements --- p.vi / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Medical Visualization System --- p.4 / Chapter 1.1.1 --- Data Acquisition --- p.4 / Chapter 1.1.2 --- Computer-aided Medical Visualization --- p.5 / Chapter 1.1.3 --- Existing Systems --- p.6 / Chapter 1.2 --- Research Goal --- p.8 / Chapter 1.2.1 --- System Architecture --- p.9 / Chapter 1.3 --- Organization of this Thesis --- p.10 / Chapter 2 --- Volume Visualization --- p.11 / Chapter 2.1 --- Sampling Grid and Volume Representation --- p.11 / Chapter 2.2 --- Priori Work in Volume Rendering --- p.13 / Chapter 2.2.1 --- Surface VS Direct --- p.14 / Chapter 2.2.2 --- Image-order VS Object-order --- p.18 / Chapter 2.2.3 --- Orthogonal VS Perspective --- p.22 / Chapter 2.2.4 --- Hardware Acceleration VS Software Acceleration --- p.23 / Chapter 2.3 --- Chapter Summary --- p.29 / Chapter 3 --- IsoRegion Leaping Technique for Perspective Volume Rendering --- p.30 / Chapter 3.1 --- Compositing Projection in Direct Volume Rendering --- p.31 / Chapter 3.2 --- IsoRegion Leaping Acceleration --- p.34 / Chapter 3.2.1 --- IsoRegion Definition --- p.35 / Chapter 3.2.2 --- IsoRegion Construction --- p.37 / Chapter 3.2.3 --- IsoRegion Step Table --- p.38 / Chapter 3.2.4 --- Ray Traversal Scheme --- p.41 / Chapter 3.3 --- Experiment Result --- p.43 / Chapter 3.4 --- Improvement --- p.47 / Chapter 3.5 --- Chapter Summary --- p.48 / Chapter 4 --- Parallel Volume Rendering by Distributed Processing --- p.50 / Chapter 4.1 --- Multi-platform Loosely-coupled Parallel Environment Shell --- p.51 / Chapter 4.2 --- Distributed Rendering Pipeline (DRP) --- p.55 / Chapter 4.2.1 --- Network Architecture of a Loosely-Coupled System --- p.55 / Chapter 4.2.2 --- Data and Task Partitioning --- p.58 / Chapter 4.2.3 --- Communication Pattern and Analysis --- p.59 / Chapter 4.3 --- Load Balancing --- p.69 / Chapter 4.4 --- Heterogeneous Rendering --- p.72 / Chapter 4.5 --- Chapter Summary --- p.73 / Chapter 5 --- User Interface --- p.74 / Chapter 5.1 --- System Design --- p.75 / Chapter 5.2 --- 3D Pen Input Device --- p.76 / Chapter 5.3 --- Visualization Environment Integration --- p.77 / Chapter 5.4 --- User Interaction: Interactive Navigation --- p.78 / Chapter 5.4.1 --- Camera Model --- p.79 / Chapter 5.4.2 --- Zooming --- p.81 / Chapter 5.4.3 --- Image View --- p.82 / Chapter 5.4.4 --- User Control --- p.83 / Chapter 5.5 --- Chapter Summary --- p.87 / Chapter 6 --- Conclusion --- p.88 / Chapter 6.1 --- Final Summary --- p.88 / Chapter 6.2 --- Deficiency and Improvement --- p.89 / Chapter 6.3 --- Future Research Aspect --- p.91 / Appendix --- p.93 / Chapter A --- Common Error in Pre-multiplying Color and Opacity --- p.94 / Chapter B --- Binary Factorization of the Sample Composition Equation --- p.96

by Man-lee Liu. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1998. / Includes bibliographical references (leaves 143-151). / LIST OF TABLES --- p.vi / LIST OF FIGURES --- p.xii / CHAPTER / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Model-based Motion Analysis --- p.2 / Chapter 1.1.1 --- With 3D-to-3D Point Correspondences --- p.4 / Chapter 1.1.2 --- With 2D-to-3D Point Correspondences --- p.5 / Chapter 1.1.3 --- With 2D-to-2D Point Correspondences --- p.6 / Chapter 1.2 --- Motion-based Segmentation --- p.7 / Chapter 1.3 --- 3D Object Recognition --- p.8 / Chapter 1.4 --- Organization of the Thesis --- p.8 / Chapter 2 --- Literature Review and Summary of Contributions --- p.10 / Chapter 2.1 --- Model-based Motion Analysis --- p.10 / Chapter 2.1.1 --- With 3D-to-3D Point Correspondences --- p.10 / Chapter 2.1.2 --- With 2D-to-3D Point Correspondences --- p.13 / Chapter 2.1.2.1 --- An Iterative Approach: Lowe's Algorithm --- p.18 / Chapter 2.1.2.2 --- A Linear Approach: Faugeras's Algorithm --- p.19 / Chapter 2.1.3 --- With 2D-to-2D Point Correspondences --- p.22 / Chapter 2.2 --- Motion-based Segmentation --- p.27 / Chapter 2.3 --- 3D Object Recognition --- p.28 / Chapter 2.4 --- Summary of Contributions --- p.30 / Chapter 3 --- Model-based Motion Analysis with 2D-to-3D Point Correspondences --- p.34 / Chapter 3.1 --- A new Iterative Algorithm for the Perspective-4-point Problem: TL-algorithm --- p.34 / Chapter 3.1.1 --- Algorithm --- p.35 / Chapter 3.1.2 --- Experiment --- p.37 / Chapter 3.1.2.1 --- Experiment using Synthetic Data --- p.38 / Chapter 3.1.2.2 --- Experiment using Real Data --- p.42 / Chapter 3.2 --- An Enhancement of Faugeras's Algorithm --- p.42 / Chapter 3.2.1 --- Experimental Comparison between the Original Faugeras's Algorithm and the Modified One --- p.44 / Chapter 3.2.1.1 --- Experiment One: Fixed Motion --- p.44 / Chapter 3.2.1.2 --- Experiment Two: Using Motion Generated Ran- domly --- p.50 / Chapter 3.2.2 --- Discussion --- p.54 / Chapter 3.3 --- A new Linear Algorithm for the Model-based Motion Analysis: Six-point Algorithm --- p.55 / Chapter 3.3.1 --- General Information of the Six-point Algorithm --- p.55 / Chapter 3.3.2 --- Original Version of the Six-point Algorithm --- p.56 / Chapter 3.3.2.1 --- Linear Solution Part --- p.56 / Chapter 3.3.2.2 --- Constraint Satisfaction --- p.58 / Use of Representation of Rotations by Quaternion --- p.62 / Use of Singular Value Decomposition --- p.62 / Determination of the translational matrix --- p.63 / Chapter 3.3.3 --- Second Version of the Six-point Algorithm --- p.64 / Chapter 3.3.4 --- Experiment --- p.65 / Chapter 3.3.4.1 --- With Synthetic Data --- p.66 / Experiment One: With Fixed Motion --- p.66 / Experiment Two: With Motion Generated Randomly --- p.77 / Chapter 3.3.4.2 --- With Real Data --- p.93 / Chapter 3.3.5 --- Summary of the Six-Point Algorithm --- p.93 / Chapter 3.3.6 --- A Visual Tracking System by using Six-point Algorithm --- p.95 / Chapter 3.4 --- Comparison between TL-algorithm and Six-point Algorithm developed --- p.97 / Chapter 3.5 --- Summary --- p.102 / Chapter 4 --- Motion-based Segmentation --- p.104 / Chapter 4.1 --- A new Approach with 3D-to-3D Point Correspondences --- p.104 / Chapter 4.1.1 --- Algorithm --- p.105 / Chapter 4.1.2 --- Experiment --- p.109 / Chapter 4.2 --- A new Approach with 2D-to-3D Point Correspondences --- p.112 / Chapter 4.2.1 --- Algorithm --- p.112 / Chapter 4.2.2 --- Experiment --- p.116 / Chapter 4.2.2.1 --- Experiment using synthetic data --- p.116 / Chapter 4.2.2.2 --- Experiment using real image sequence --- p.119 / Chapter 4.3 --- Summary --- p.119 / Chapter 5 --- 3D Object Recognition --- p.121 / Chapter 5.1 --- Proposed Algorithm for the 3D Object Recognition --- p.122 / Chapter 5.1.1 --- Hypothesis step --- p.122 / Chapter 5.1.2 --- Verification step --- p.124 / Chapter 5.2 --- 3D Object Recognition System --- p.125 / Chapter 5.2.1 --- System in Matlab: --- p.126 / Chapter 5.2.2 --- System in Visual C++ --- p.129 / Chapter 5.3 --- Experiment --- p.131 / Chapter 5.3.1 --- System in Matlab --- p.132 / Chapter 5.3.2 --- System in Visual C++ --- p.136 / Chapter 5.4 --- Summary --- p.139 / Chapter 6 --- Conclusions --- p.140 / REFERENCES --- p.142 / APPENDIX / Chapter A --- Representation of Rotations by Quaternion --- p.152 / Chapter B --- Constrained Optimization --- p.154

Lee, Kai Ki. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 163-183). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts also in Chinese.

Layered manufacturing plays important role in industry. Conventional pro-cess planning takes polygon soup as input and has high quality requirements on these polygonal model such as no self-intersection, no degenerate polygon et al. A growing number of models, especially for those in complex shape are acquired from reverse engineering. Implicit representation always serves as intermediate representation and ¯nally need to be tesselated into polygonal mesh for layered manufacturing applications. However, the present tessellation techniques have difficulties to provide topologically faithful and self-intersection free polygonal mesh from implicit model. On the other hand, implicit representation are mathematically compact and robust, which is important for presenting complex freeform models. / I develop a robust and efficient approach to directly slicing implicit solids. Different from prior slicing techniques that reconstruct contours on the slicing plane by tracing the topology of intersected line segments, which is actually not robust, I generate contours through a topology guaranteed contour extraction on binary images sampled from given solids and a subsequent contour simplification algorithm which has the topology preserved and the geometric error controlled. The resultant contours are free of self-intersection, topologically faithful to the given r-regular solids and with shape error bounded; therefore, correct objects can be fabricated from them by layered manufacturing. Moreover, since I do not need to generate the tessellated B-rep of given solids, my direct slicing approach is memory efficient - only the binary image and the finest contours on one particular slicing plane need to be stored in-core. My method is general and can be applied to any implicit representations of solids. / Moreover, I also investigate techniques for support generation for layered manufacturing in image space. Region subtraction is a crucial operation for support generation. I develop a robust and reliable region subtraction method on implicit solid slicing. Compared with the conventional approach in which support regioncontours are produced from part slicing contours by polygonal operations, my approach calculates reasonable support region on binary image for each layer. I investigate a conservative growing-swallow technique to remove as much as possible the support material for self-support region while still guarantee the safety of building process. My region subtraction can serve as core technique for many layered manufacturing processes. In my research, I demonstrate region subtraction technique in both Fused Decomposition Modeling(FDM) and Stereolithography(SLA). A region cleaning technique which can reduce topology complexity of calculated support structure region is developed to fulfil specific requirement of FDM. With all the operations involved being discrete on binary image, my approach is more robust compared with the polygonal operations which are based on numerical computation. Moreover, processing on binary image makes my approach highly parallelizable. My self-intersection free contour extraction technique used in direct slicing can also be adopted to extract support structure contour on binary image if necessary. / Huang, Pu. / "October 2012." / Thesis (M.Phil.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 80-84). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract --- p.i / Chinese Abstract --- p.iii / Acknowledgements --- p.iv / List of Figures --- p.vii / List of Tables --- p.ix / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Introduction --- p.1 / Chapter 1.2 --- Contribution --- p.4 / Chapter 1.3 --- Organization --- p.5 / Chapter 2 --- Literature Review --- p.7 / Chapter 2.1 --- Direct Slicing on Implicit Solid --- p.7 / Chapter 2.2 --- Slicing based Support Generation --- p.9 / Chapter 3 --- Problem Definition --- p.10 / Chapter 4 --- Topologically Faithful Slicing Contour Generation --- p.12 / Chapter 4.1 --- Introduction --- p.12 / Chapter 4.2 --- Sampling and Contour Generation --- p.15 / Chapter 4.2.1 --- Sampling --- p.16 / Chapter 4.2.2 --- Topologically faithful contouring --- p.17 / Chapter 4.2.3 --- r-Regularity and Accuracy in Layered Manufacturing --- p.19 / Chapter 4.3 --- Constrained Smoothing --- p.20 / Chapter 4.4 --- Contour Simplification --- p.24 / Chapter 4.4.1 --- Variational segmentation --- p.25 / Chapter 4.4.2 --- Topology and distortion verification --- p.27 / Chapter 4.4.3 --- Hausdorff Error Analysis --- p.31 / Chapter 4.5 --- Results and Discussion --- p.33 / Chapter 5 --- Reliable and Robust Region Subtraction for Support Generation --- p.43 / Chapter 5.1 --- Introduction --- p.43 / Chapter 5.2 --- Preliminary --- p.46 / Chapter 5.3 --- Region Subtraction --- p.48 / Chapter 5.3.1 --- Binary Image Grid-width and Self-support Feature Threshold --- p.48 / Chapter 5.3.2 --- Conservative Growing-swallow Method --- p.50 / Chapter 5.4 --- Region Cleaning Technique for FDM --- p.53 / Chapter 5.5 --- Anchor Support Generation for SLA --- p.57 / Chapter 5.6 --- Result and Discussion --- p.60 / Chapter 6 --- Conclusion --- p.71 / Chapter 6.1 --- Summary and Discussion --- p.71 / Chapter 6.2 --- Future Work --- p.73 / Chapter A --- Inconsistent Contouring Problem Analysis --- p.76 / Bibliography --- p.80

Dimensional Stacking is a technique for displaying multivariate data in two dimensional screen space. This technique involves the discretization and recursive embedding of dimensions, each resulting N-dimensional bin occupying a unique position on the screen. This thesis describes the extension of this technique to a three dimensional projection. In addition to the visual enhancements, hashing was used to improve the scalability of records and dimensions. The resulting visualization was evaluated by a usability study.

by Po-Ming Wong. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1997. / Includes bibliographical references (leaves 94-100). / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Introduction --- p.1 / Chapter 1.2 --- Image Data --- p.2 / Chapter 1.2.1 --- Feature Detection --- p.2 / Chapter 1.3 --- Neural Networks --- p.4 / Chapter 1.4 --- Invariant Object Recognition --- p.5 / Chapter 1.5 --- Thesis Outline --- p.7 / Chapter 2 --- Feature Extraction --- p.8 / Chapter 2.1 --- Review of the Principle Component Analysis (PCA) Method --- p.9 / Chapter 2.1.1 --- Theory --- p.10 / Chapter 2.2 --- Covariance Operator --- p.13 / Chapter 2.3 --- Corner Extraction Method --- p.16 / Chapter 2.3.1 --- Corner Detection on the Surface of an Object --- p.16 / Chapter 2.3.2 --- Corner Detection at Boundary Region --- p.17 / Chapter 2.3.3 --- Steps in Corner Detection Process --- p.21 / Chapter 2.4 --- Experiment Results and Discussion --- p.23 / Chapter 2.4.1 --- Features Localization --- p.27 / Chapter 2.4.2 --- Preparing Feature Points for Matching Process --- p.32 / Chapter 2.5 --- Summary --- p.32 / Chapter 3 --- Invariant Graph Matching Using High-Order Hopfield Network --- p.36 / Chapter 3.1 --- Review of the Hopfield Network --- p.37 / Chapter 3.1.1 --- 3D Image Matching Algorithm --- p.40 / Chapter 3.1.2 --- Iteration Algorithm --- p.44 / Chapter 3.2 --- Third-order Hopfield Network --- p.45 / Chapter 3.3 --- Experimental Results --- p.49 / Chapter 3.4 --- Summary --- p.58 / Chapter 4 --- Hopfield Network for 2D and 3D Mirror-Symmetric Image Match- ing --- p.59 / Chapter 4.1 --- Introduction --- p.59 / Chapter 4.2 --- Geometric Symmetry --- p.60 / Chapter 4.3 --- Motivation --- p.62 / Chapter 4.4 --- Third-order Hopfield Network for Solving 2D Symmetry Problems --- p.66 / Chapter 4.5 --- Forth-order Hopfield Network for Solving 3D Symmetry Problem --- p.71 / Chapter 4.6 --- Experiment Results --- p.78 / Chapter 4.7 --- Summary --- p.88 / Chapter 5 --- Conclusion --- p.90 / Chapter 5.1 --- Results and Contributions --- p.90 / Chapter 5.2 --- Future Work --- p.92 / Bibliography --- p.94

Chou Yun-Sum, Bailey. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves 89-92). / Abstracts in English and Chinese. / List of Symbol / Chapter Chapter 1 --- Introduction / Chapter 1.1 --- The Goal: Euclidean Reconstruction --- p.1 / Chapter 1.2 --- Historical background --- p.2 / Chapter 1.3 --- Scope of the thesis --- p.2 / Chapter 1.4 --- Thesis Outline --- p.3 / Chapter Chapter 2 --- An introduction to stereo vision and 3D shape reconstruction / Chapter 2.1 --- Homogeneous Coordinates --- p.4 / Chapter 2.2 --- Camera Model / Chapter 2.2.1 --- Pinhole Camera Model --- p.5 / Chapter 2.3 --- Camera Calibration --- p.11 / Chapter 2.4 --- Geometry of Binocular System --- p.14 / Chapter 2.5 --- Stereo Matching --- p.15 / Chapter 2.5.1 --- Accuracy of Corresponding Point --- p.17 / Chapter 2.5.2 --- The Stereo Matching Approach --- p.18 / Chapter 2.5.2.1 --- Intensity-based stereo matching --- p.19 / Chapter 2.5.2.2 --- Feature-based stereo matching --- p.20 / Chapter 2.5.3 --- Matching Constraints --- p.20 / Chapter 2.6 --- 3D Reconstruction --- p.22 / Chapter 2.7 --- Recent development on self calibration --- p.24 / Chapter 2.8 --- Summary of the Chapter --- p.25 / Chapter Chapter 3 --- Camera Calibration / Chapter 3.1 --- Introduction --- p.26 / Chapter 3.2 --- Camera Self-calibration --- p.27 / Chapter 3.3 --- Self-calibration under general camera motion --- p.27 / Chapter 3.3.1 --- The absolute Conic Based Techniques --- p.28 / Chapter 3.3.2 --- A Stratified approach for self-calibration by Pollefeys --- p.33 / Chapter 3.3.3 --- Pollefeys self-calibration with Absolute Quadric --- p.34 / Chapter 3.3.4 --- Newsam's self-calibration with linear algorithm --- p.34 / Chapter 3.4 --- Camera Self-calibration under specially designed motion sequence / Chapter 3.4. 1 --- Hartley's self-calibration by pure rotations --- p.35 / Chapter 3.4.1.1 --- Summary of the Algorithm / Chapter 3.4.2 --- Pollefeys self-calibration with variant focal length --- p.36 / Chapter 3.4.2.1 --- Summary of the Algorithm / Chapter 3.4.3 --- Faugeras self-calibration of a 1D Projective Camera --- p.38 / Chapter 3.5 --- Summary of the Chapter --- p.39 / Chapter Chapter 4 --- Self-calibration under Planar motions / Chapter 4.1 --- Introduction --- p.40 / Chapter 4.2 --- 1D Projective Camera Self-calibration --- p.41 / Chapter 4.2.1 --- 1-D camera model --- p.42 / Chapter 4.2.2 --- 1-D Projective Camera Self-calibration Algorithms --- p.44 / Chapter 4.2.3 --- Planar motion detection --- p.45 / Chapter 4.2.4 --- Self-calibration under horizontal planar motions --- p.46 / Chapter 4.2.5 --- Self-calibration under three different planar motions --- p.47 / Chapter 4.2.6 --- Result analysis on self-calibration Experiments --- p.49 / Chapter 4.3 --- Essential Matrix and Triangulation --- p.51 / Chapter 4.4 --- Merge of Partial 3D models --- p.51 / Chapter 4.5 --- Summary of the Reconstruction Algorithms --- p.53 / Chapter 4.6 --- Experimental Results / Chapter 4.6.1 --- Experiment 1 : A Simulated Box --- p.54 / Chapter 4.6.2 --- Experiment 2 : A Real Building --- p.57 / Chapter 4.6.3 --- Experiment 3 : A Sun Flower --- p.58 / Chapter 4.7 --- Conclusion --- p.59 / Chapter Chapter 5 --- Building Reconstruction using a linear camera self- calibration technique / Chapter 5.1 --- Introduction --- p.60 / Chapter 5.2 --- Metric Reconstruction from Partially Calibrated image / Chapter 5.2.1 --- Partially Calibrated Camera --- p.62 / Chapter 5.2.2 --- Optimal Computation of Fundamental Matrix (F) --- p.63 / Chapter 5.2.3 --- Linearly Recovering Two Focal Lengths from F --- p.64 / Chapter 5.2.4 --- Essential Matrix and Triangulation --- p.66 / Chapter 5.3 --- Experiments and Discussions --- p.67 / Chapter 5.4 --- Conclusion --- p.71 / Chapter Chapter 6 --- Refine the basic model with detail depth information by a Model-Based Stereo technique / Chapter 6.1 --- Introduction --- p.72 / Chapter 6.2 --- Model Based Epipolar Geometry / Chapter 6.2.1 --- Overview --- p.74 / Chapter 6.2.2 --- Warped offset image preparation --- p.76 / Chapter 6.2.3 --- Epipolar line calculation --- p.78 / Chapter 6.2.4 --- Actual corresponding point finding by stereo matching --- p.80 / Chapter 6.2.5 --- Actual 3D point generated by Triangulation --- p.80 / Chapter 6.3 --- Summary of the Algorithms --- p.81 / Chapter 6.4 --- Experiments and discussions --- p.83 / Chapter 6.5 --- Conclusion --- p.85 / Chapter Chapter 7 --- Conclusions / Chapter 7.1 --- Summary --- p.86 / Chapter 7.2 --- Future Work --- p.88 / BIBLIOGRAPHY --- p.89