Wang, Tianming. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 59-62). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts also in Chinese.

published_or_final_version / abstract / Computer Science / Doctoral / Doctor of Philosophy

published_or_final_version / abstract / Computer Science / Master / Master of Philosophy

Zhao, Ming. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (p. 111-117) and index. / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation --- p.1 / Chapter 1.2 --- Objective of the study --- p.2 / Chapter 1.3 --- Challenges and our approach --- p.4 / Chapter 1.4 --- Original contributions --- p.6 / Chapter 1.5 --- Organization of this dissertation --- p.6 / Chapter 2 --- Related Work --- p.9 / Chapter 2.1 --- Critical configuration for motion estimation and projective reconstruction --- p.9 / Chapter 2.1.1 --- Point feature --- p.9 / Chapter 2.1.2 --- Line feature --- p.12 / Chapter 2.2 --- Camera motion estimation --- p.14 / Chapter 2.2.1 --- Line tracking --- p.15 / Chapter 2.2.2 --- Determining camera motion --- p.19 / Chapter 3 --- Preliminaries on Three-View Geometry and Trifocal Tensor --- p.23 / Chapter 3.1 --- Projective spaces P3 and transformations --- p.23 / Chapter 3.2 --- The trifocal tensor --- p.24 / Chapter 3.3 --- Computation of the trifocal tensor-Normalized linear algorithm --- p.31 / Chapter 4 --- Linear Line Structures --- p.33 / Chapter 4.1 --- Models of line space --- p.33 / Chapter 4.2 --- Line structures --- p.35 / Chapter 4.2.1 --- Linear line space --- p.37 / Chapter 4.2.2 --- Ruled surface --- p.37 / Chapter 4.2.3 --- Line congruence --- p.38 / Chapter 4.2.4 --- Line complex --- p.38 / Chapter 5 --- Critical Configurations of Three Views Revealed by Line Correspondences --- p.41 / Chapter 5.1 --- Two-view degeneracy --- p.41 / Chapter 5.2 --- Three-view degeneracy --- p.42 / Chapter 5.2.1 --- Introduction --- p.42 / Chapter 5.2.2 --- Linear line space --- p.44 / Chapter 5.2.3 --- Linear ruled surface --- p.54 / Chapter 5.2.4 --- Linear line congruence --- p.55 / Chapter 5.2.5 --- Linear line complex --- p.57 / Chapter 5.3 --- Retrieving tensor in critical configurations --- p.60 / Chapter 5.4 --- Rank classification of non-linear line structures --- p.61 / Chapter 6 --- Camera Motion Estimation Framework --- p.63 / Chapter 6.1 --- Line extraction --- p.64 / Chapter 6.2 --- Line tracking --- p.65 / Chapter 6.2.1 --- Preliminary geometric tracking --- p.65 / Chapter 6.2.2 --- Experimental results --- p.69 / Chapter 6.3 --- Camera motion estimation framework using EKF --- p.71 / Chapter 7 --- Experimental Results --- p.75 / Chapter 7.1 --- Simulated data experiments --- p.75 / Chapter 7.2 --- Real data experiments --- p.76 / Chapter 7.2.1 --- Linear line space --- p.80 / Chapter 7.2.2 --- Linear ruled surface --- p.84 / Chapter 7.2.3 --- Linear line congruence --- p.84 / Chapter 7.2.4 --- Linear line complex --- p.91 / Chapter 7.3 --- Empirical observation: ruled plane for line transfer --- p.93 / Chapter 7.4 --- Simulation for non-linear line structures --- p.94 / Chapter 8 --- Conclusions and Future Work --- p.97 / Chapter 8.1 --- Summary --- p.97 / Chapter 8.2 --- Future work --- p.99 / Chapter A --- Notations --- p.101 / Chapter B --- Tensor --- p.103 / Chapter C --- Matrix Decomposition and Estimation Techniques --- p.104 / Chapter D --- MATLAB Files --- p.107 / Chapter D.1 --- Estimation matrix --- p.107 / Chapter D.2 --- Line transfer --- p.109 / Chapter D.3 --- Simulation --- p.109

This thesis introduces novel methods for estimating the poses of a reference plane from its reflections for specular surface recovery. Traditional methods for specular surface recovery usually introduce a second camera and an auxiliary calibration pattern to calibrate the poses of the reference plane with respect to the camera. The calibration procedures are comparatively tedious. Auto-estimating the poses of the reference plane is therefore an appealing problem. In the first part of this thesis, two novel and practical methods are proposed to recover the poses of a moving reference plane from its reflections produced on the specular surface given its initial position. As for the first approach, the reference plane is constrained to undergo an unknown pure translation. By observing the reflections of the moving reference plane produced on the specular surface, a closed form solution is derived for recovering the unknown translation. Degenerate cases in which the proposed method fails are studied. As for the second approach, the constraint on the motion of the reference plane is removed, and the reference plane can move freely. Again, a closed form solution is derived for the unknown motion defined by a rotation matrix and a translation vector, and the degenerate cases are also presented. The thesis finally considers the problem for auto-calibrating the reference plane against the camera for specular surface recovery without prior knowledge of the reference plane’s initial position. By only observing its reflections produced on the specular surface, the poses of the reference planes can be recovered in two steps. First, by applying a collinearity constraint to the specular correspondences, a simple closed form solution is derived for recovering the poses of the reference plane relative to its initial pose. Second, by applying a ray incidence constraint to the incident rays formed by the specular correspondences and the visual rays cast from the image, a closed form solution is derived for recovering the poses of the reference plane relative to the camera. The shape of the specular surface then follows. / published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy

Wang Tong. / Thesis submitted in: June 2004. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 64-69). / Abstracts in English and Chinese. / ABSTRACT --- p.I / 摘要 --- p.IV / ACKNOWLEDGMENTS --- p.VI / TABLE OF CONTENTS --- p.VIII / LIST OF FIGURES --- p.XIIV / Chapter CHAPTER 1 --- INTRODUCTION --- p.1 / Chapter 1.1 --- Hough Transform --- p.2 / Chapter 1.2 --- Template Matching --- p.3 / Chapter 1.3 --- Genetic Algorithms --- p.4 / Chapter 1.4 --- Outline of the Thesis --- p.6 / Chapter CHAPTER 2 --- HOUGH TRANSFORM AND ITS COMMON VARIANTS --- p.7 / Chapter 2.1 --- Hough Transform --- p.7 / Chapter 2.1.1 --- What is Hough Transform --- p.7 / Chapter 2.1.2 --- Parameter Space --- p.7 / Chapter 2.1.3 --- Accumulator Array --- p.9 / Chapter 2.2 --- Gradient-based Hough Transform --- p.10 / Chapter 2.2.1 --- Direction of Gradient --- p.11 / Chapter 2.2.2 --- Accumulator Array --- p.14 / Chapter 2.2.3 --- Peaks in the accumulator array --- p.16 / Chapter 2.2.4 --- Performance of Gradient-based Hough Transform --- p.18 / Chapter 2.3 --- Generalized Hough Transform (GHT) --- p.19 / Chapter 2.3.1 --- What Is GHT --- p.19 / Chapter 2.3.2 --- R-table of GHT --- p.20 / Chapter 2.3.3 --- GHT Procedure --- p.21 / Chapter 2.3.4 --- Analysis --- p.24 / Chapter 2.4 --- Edge Detection --- p.25 / Chapter 2.4.1 --- Gradient-Based Method --- p.25 / Chapter 2.4.2 --- Laplacian of Gaussian --- p.29 / Chapter 2.4.3 --- Canny edge detection --- p.30 / Chapter CHAPTER 3 --- PROBABILISTIC MODELS --- p.33 / Chapter 3.1 --- Randomized Hough Transform (RHT) --- p.33 / Chapter 3.1.1 --- Basics of the RHT --- p.33 / Chapter 3.1.2 --- RHT algorithm --- p.34 / Chapter 3.1.3 --- Advantage of RHT --- p.37 / Chapter 3.2 --- Genetic Model --- p.37 / Chapter 3.2.1 --- Genetic algorithm mechanism --- p.38 / Chapter 3.2.2 --- A Genetic Algorithm for Primitive Extraction --- p.39 / Chapter CHAPTER 4 --- PROPOSED ARBITRARY SHAPE DETECTION --- p.42 / Chapter 4.1 --- Randomized Generalized Hough Transform --- p.42 / Chapter 4.1.1 --- R-table properties and the general notion of a shape --- p.42 / Chapter 4.1.2 --- Using pairs of edges --- p.44 / Chapter 4.1.3 --- Extend to Arbitrary shapes --- p.46 / Chapter 4.2 --- A Genetic algorithm with the Hausdorff distance --- p.47 / Chapter 4.2.1 --- Hausdorff distance --- p.47 / Chapter 4.2.2 --- Chromosome strings --- p.48 / Chapter 4.2.3 --- Discussion --- p.51 / Chapter CHAPTER 5 --- EXPERIMENTAL RESULTS AND COMPARISONS --- p.52 / Chapter 5.1 --- Primitive extraction --- p.53 / Chapter 5.2 --- Arbitrary Shape Detection --- p.54 / Chapter 5.3 --- Summary of the Experimental Results --- p.60 / Chapter CHAPTER 6 --- CONCLUSIONS --- p.62 / Chapter 6.1 --- Summary --- p.62 / Chapter 6.2 --- Future work --- p.63 / BIBLIOGRAPHY --- p.64

基於審美的圖像質量自動評估近年來引起了計算機視覺領域的普遍關注。在這篇論文裡, 我們提出使用局部與整體特徵, 基於圖像內容進行圖片質量評估。首先, 圖像的主題區域被提取出來。這部分區域最吸引觀看者的注意力。基於主題區域, 我們提取局部特徵, 並結合整體特徵進行圖像質量評估。攝影專家拍攝圖片時, 對於不同內容的圖片, 會採取不同的技術手段和審美衡量標準。基於此項觀察, 我們提出根據圖片的內容, 在提取主題區域以及特徵的時候採用不同的手段。我們講數據根據圖像內容分為七類, 並分別設計主題區域提取方法和設計特徵。我們通過翔實的實驗數據，證明提出的框架之有效。 / 同時, 我們提出根據圖像內容特徵構建自適應分類器, 以在不事先知道圖像內容分類的情況下進行自動質量評估, 並取得滿意效果。 / Automatically assessing photo quality from the perspective of visual aesthetics is of great interest in high-level vision research and has drawn much attention in recent years. In this paper, we propose content-based photo quality assessment using both regional and global features. Under this framework, subject areas, which draw the most attentions of human eyes, are first extracted. Then regional features extracted both from subject areas and background regions are combined with global features to assess photo quality. Since professional photographers adopt different photographic techniques and have different aesthetic criteria in mind when taking different types of photos (e.g. landscape versus portrait), we propose to segment subject areas and extract visual features in different ways according to the variety of photo content. We divide the photos into seven categories based on the irvisual content and develop a set of new subject are a extraction methods and new visual features specially designed for different categories. / This argument is supported by extensive experimental comparisons of existing photo quality assessment approaches as well as our new features over different categories of photos. In addition, we propose an approach of online training an adaptive classifier to combine the proposed features according to the visual content of a test photo without knowing its category. Another contribution of this work is to construct a large and diversified benchmark database for the research of photo quality assessment. It includes 17, 613 photos with manually labeled ground truth. This new benchmark database will be released to the research community. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Luo, Wei. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 47-52). / Abstracts also in Chinese. / Chapter Abstract --- p.i / Chapter Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Photo Quality Assessment by Professionals --- p.2 / Chapter 1.2 --- Automatic Quality Assessment --- p.6 / Chapter 1.3 --- Our Approach --- p.8 / Chapter 2 --- RelatedWork --- p.12 / Chapter 3 --- Content-based Quality Assessment --- p.15 / Chapter 3.1 --- Global Features --- p.15 / Chapter 3.1.1 --- Hue Composition Feature --- p.15 / Chapter 3.1.2 --- Scene Composition Feature --- p.19 / Chapter 3.2 --- Subject Area Extraction Methods --- p.21 / Chapter 3.2.1 --- Clarity-Based Subject Area Extraction --- p.22 / Chapter 3.2.2 --- Layout-Based Subject Area Extraction --- p.25 / Chapter 3.2.3 --- Human-Based Subject Area Extraction --- p.25 / Chapter 3.3 --- Regional Features --- p.25 / Chapter 3.3.1 --- Dark Channel Feature --- p.27 / Chapter 3.3.2 --- Clarity Contrast Feature --- p.28 / Chapter 3.3.3 --- Lighting Contrast Feature --- p.30 / Chapter 3.3.4 --- Composition Geometry Feature --- p.30 / Chapter 3.3.5 --- Complexity Features --- p.31 / Chapter 3.3.6 --- Human Based Features --- p.31 / Chapter 3.4 --- Quality Assessment without the Information of Photo Categories --- p.33 / Chapter 4 --- Experimental Results --- p.37 / Chapter 4.1 --- Database description --- p.37 / Chapter 4.2 --- Experimental Settings --- p.40 / Chapter 4.3 --- Result Analysis --- p.41 / Chapter 4.4 --- Conclusions and Discussions --- p.44 / Bibliography --- p.47

Pun Chi Man. / "July 2002." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (p. 119-127). / 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. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

Shan, Qi. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 124-132). / Abstracts in English and Chinese. / Chapter 1 --- Overview --- p.1 / Chapter 1.1 --- Image Blur Overview --- p.1 / Chapter 1.2 --- Blur Identification in a Transparency's Perspective --- p.3 / Chapter 1.3 --- From Transparencies to Natural Image Priors --- p.7 / Chapter 1.4 --- Discussion of the Linear Motion Model --- p.9 / Chapter 1.5 --- Binary Texture Restoration and High-Order MRF Optimization --- p.9 / Chapter 2 --- A Review on Previous Work --- p.13 / Chapter 2.1 --- Spatially-Invariant Blur Recovery --- p.13 / Chapter 2.2 --- Spatially-Variant Blur Recovery --- p.16 / Chapter 2.3 --- Markov Random Field Inference --- p.18 / Chapter 3 --- Motion Blur in a Transparency's Perspective --- p.20 / Chapter 3.1 --- Analysis of Object Motion Blur --- p.20 / Chapter 3.1.1 --- 1D Object Motion Blur --- p.20 / Chapter 3.1.2 --- 2D Object Motion Blur --- p.23 / Chapter 3.2 --- Modeling 2D Object Motion Blur --- p.26 / Chapter 3.3 --- Optimization Procedure --- p.27 / Chapter 3.3.1 --- Blur Kernel Estimation --- p.29 / Chapter 3.3.2 --- Latent Binary Matte Estimation --- p.30 / Chapter 3.4 --- Generalized Transparency in Motion Blur --- p.33 / Chapter 3.4.1 --- Camera Motion Blur Estimation --- p.35 / Chapter 3.4.2 --- Implementation --- p.37 / Chapter 3.5 --- Analysis and Results --- p.38 / Chapter 3.5.1 --- Evaluation of the Kernel Initialization --- p.40 / Chapter 3.5.2 --- Evaluation of Binary Alpha Initialization --- p.40 / Chapter 3.5.3 --- Robustness to Noise --- p.41 / Chapter 3.5.4 --- Natural Image Deblurring Results --- p.41 / Chapter 3.6 --- Proofs --- p.50 / Chapter 4 --- Rotational Motion Deblurring --- p.55 / Chapter 4.1 --- Motion blur descriptor --- p.55 / Chapter 4.1.1 --- Descriptor analysis --- p.56 / Chapter 4.2 --- Optimization --- p.59 / Chapter 4.2.1 --- Parameter initialization --- p.59 / Chapter 4.2.2 --- Iterative optimization --- p.62 / Chapter 4.2.3 --- Recover the color image --- p.65 / Chapter 4.3 --- Result and analysis --- p.65 / Chapter 5 --- Image Deblurring using Natural Image Priors --- p.70 / Chapter 5.1 --- Problem Definition --- p.70 / Chapter 5.2 --- Analysis of Ringing Artifacts --- p.71 / Chapter 5.3 --- Our model --- p.74 / Chapter 5.3.1 --- Definition of the probability terms --- p.75 / Chapter 5.4 --- Optimization --- p.81 / Chapter 5.4.1 --- Optimizing L --- p.83 / Chapter 5.4.2 --- Optimizing f --- p.86 / Chapter 5.4.3 --- Optimization Details and Parameters --- p.87 / Chapter 5.5 --- Experimental Results --- p.90 / Chapter 6 --- High Order MRF and its Optimization --- p.94 / Chapter 6.1 --- The Approach --- p.95 / Chapter 6.1.1 --- Polynomial Standardization --- p.95 / Chapter 6.1.2 --- Polynomial Graph Construction --- p.97 / Chapter 6.1.3 --- Polynomial Graph Partition --- p.103 / Chapter 6.1.4 --- Multi-Label Expansion --- p.105 / Chapter 6.1.5 --- Analysis --- p.106 / Chapter 6.2 --- Experimental Results --- p.108 / Chapter 6.3 --- Summary --- p.112 / Chapter 6.4 --- Proofs --- p.112 / Chapter 7 --- Conclusion --- p.117 / Chapter 7.1 --- Solving Linear Motion Blur in a Transparency's Perspective --- p.117 / Chapter 7.2 --- Rotational Motion Deblurring --- p.119 / Chapter 7.3 --- Image Deblurring using Natural Image Priors --- p.119 / Chapter 7.4 --- Contribution --- p.121 / Chapter 7.5 --- Discussion and Open Questions --- p.121 / Bibliography --- p.124

Huang, Ting. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (p. 37-41). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Related Area --- p.2 / Chapter 1.2 --- Previous Work --- p.4 / Chapter 1.3 --- Proposed Framework --- p.7 / Chapter 1.4 --- Overview --- p.8 / Chapter 2 --- Markov Random Fields and Optimization Schemes --- p.9 / Chapter 2.1 --- MRF Model --- p.10 / Chapter 2.1.1 --- MAP Understanding --- p.11 / Chapter 2.2 --- Belief Propagation Optimization Scheme --- p.14 / Chapter 2.2.1 --- Max-Product BP on MRFs --- p.14 / Chapter 2.2.2 --- Sum-Product BP on MRFs --- p.15 / Chapter 3 --- Our Formulation --- p.17 / Chapter 3.1 --- An MRF Model --- p.18 / Chapter 3.2 --- Coarse-to-Fine Optimization by BP --- p.21 / Chapter 3.2.1 --- Coarse-Level Belief Propagation --- p.23 / Chapter 3.2.2 --- Fine-Level Belief Propagation --- p.24 / Chapter 3.2.3 --- Performance Enhancement --- p.25 / Chapter 4 --- Experiments --- p.27 / Chapter 4.1 --- Comparison --- p.27 / Chapter 4.2 --- Failure Case --- p.32 / Chapter 5 --- Conclusion --- p.35 / Bibliography --- p.37