The first approach, described in the first part of this thesis, studies 3D face modeling from multi-views. Today human face modeling and animation techniques are widely used to generate virtual characters and models. Such characters and models are used in movies, computer games, advertising, news broadcasting and other activities. We propose an efficient method to estimate the poses, the global shape and the local structures of a human head recorded in multiple face images or a video sequence by using a generic wireframe face model. Based on this newly proposed method, we have successfully developed a pose invariant face recognition system and a pose invariant face contour extraction method. / The objective of this thesis is to model and render complex scenes or objects from multiple images taken from different viewpoints. Two approaches to achieve this objective were investigated in this thesis. The first one is for known objects with prior geometrical models, which can be deformed to match the objects recorded in multiple input images. The second one is for general scenes or objects without prior geometrical models. / The proposed algorithms in this thesis were tested on many real and synthetic data. The experimental results illustrate their efficiency and limitations. / The second approach, described in the second part of this thesis, investigates 3D modeling and rendering for general complex scenes. The entertainment industry touches hundreds of millions of people every day, and synthetic pictures and 3D reconstruction of real scenes, often mixed with actual film footage, are now common place in computer games, sports broadcasting, TV advertising and feature films. A series of techniques has been developed to complete this task. First, a new view-ordering algorithm was proposed to organize and order an unorganized image database. Second, a novel and efficient multiview feature matching approach was developed to calibrate and track all views. Finally, both match propagation based and Bayesian based methods were developed to produce 3D scene models for rendering. / Yao Jian. / "September 2006." / Adviser: Wai-Kuen Chan. / Source: Dissertation Abstracts International, Volume: 68-03, Section: B, page: 1849. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (p. 170-181). / 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. / Abstracts in English and Chinese. / School code: 1307.

Facial expression recognition has become an active research topic in recent years due to its applications in human computer interfaces and data-driven animation. In this thesis, we focus on the problem of how to e?ectively use domain, temporal and categorical information of facial expressions to help computer understand human emotions. Over the past decades, many techniques (such as neural networks, Gaussian processes, support vector machines, etc.) have been applied to facial expression analysis. Recently graphical models have emerged as a general framework for applying probabilistic models. They provide a natural framework for describing the generative process of facial expressions. However, these models often su?er from too many latent variables or too complex model structures, which makes learning and inference di±cult. In this thesis, we will try to analyze the deformation of facial expression by introducing some recently developed graphical models (e.g. latent topic model) or improving the recognition ability of some already widely used models (e.g. HMM). In this thesis, we develop three di?erent graphical models with di?erent representational assumptions: categories being represented by prototypes, sets of exemplars and topics in between. Our ¯rst model incorporates exemplar-based representation into graphical models. To further improve computational e±- ciency of the proposed model, we build it in a local linear subspace constructed by principal component analysis. The second model is an extension of the recently developed topic model by introducing temporal and categorical information into Latent Dirichlet Allocation model. In our discriminative temporal topic model (DTTM), temporal information is integrated by placing an asymmetric Dirichlet prior over document-topic distributions. The discriminative ability is improved by a supervised term weighting scheme. We describe the resulting DTTM in detail and show how it can be applied to facial expression recognition. Our third model is a nonparametric discriminative variation of HMM. HMM can be viewed as a prototype model, and transition parameters act as the prototype for one category. To increase the discrimination ability of HMM at both class level and state level, we introduce linear interpolation with maximum entropy (LIME) and member- ship coe±cients to HMM. Furthermore, we present a general formula for output probability estimation, which provides a way to develop new HMM. Experimental results show that the performance of some existing HMMs can be improved by integrating the proposed nonparametric kernel method and parameters adaption formula. In conclusion, this thesis develops three di?erent graphical models by (i) combining exemplar-based model with graphical models, (ii) introducing temporal and categorical information into Latent Dirichlet Allocation (LDA) topic model, and (iii) increasing the discrimination ability of HMM at both hidden state level and class level. / published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy

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The aim of the diploma thesis is to analyze the current state of creation of management reporting, its contribution to a company and to create a proposal for improving and expanding awareness of reporting in a company.

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The efforts addressed in this thesis refer to assaying the extent of local features in 2D-images for the purpose of recognition and classification. It is based on comparing a test-image against a template in binary format. It is a bioinformatics-inspired approach pursued and presented as deliverables of this thesis as summarized below: 1. By applying the so-called 'Smith-Waterman (SW) local alignment' and 'Needleman-Wunsch (NW) global alignment' approaches of bioinformatics, a test 2D-image in binary format is compared against a reference image so as to recognize the differential features that reside locally in the images being compared 2. SW and NW algorithms based binary comparison involves conversion of one-dimensional sequence alignment procedure (indicated traditionally for molecular sequence comparison adopted in bioinformatics) to 2D-image matrix 3. Relevant algorithms specific to computations are implemented as MatLabTM codes 4. Test-images considered are: Real-world bio-/medical-images, synthetic images, microarrays, biometric finger prints (thumb-impressions) and handwritten signatures. Based on the results, conclusions are enumerated and inferences are made with directions for future studies. / by Deepti Pappusetty. / Thesis (M.S.C.S.)--Florida Atlantic University, 2011. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2011. Mode of access: World Wide Web.

Object recognition--"What is in this image?"--is one of the basic problems of computer vision. Most work in this area has been on finding basic-level object categories such as plant, car, and bird, but recently there has been an increasing amount of work in fine-grained visual categorization, in which the task is to recognize subcategories of a basic-level category, such as blue jay and bluebird. Experimental psychology has found that while basic-level categories are distinguished by the presence or absence of parts (a bird has a beak but car does not), subcategories are more often distinguished by the characteristics of their parts (a starling has a narrow, yellow beak while a cardinal has a wide, red beak). In this thesis we tackle fine-grained visual categorization, guided by this observation. We develop alignment procedures that let us compare corresponding parts, build classifiers tailored to finding the interclass differences at each part, and then combine the per-part classifiers to build subcategory classifiers. Using this approach, we outperform previous work in several fine-grained categorization settings: bird species identification, face recognition, and face attribute classification. In addition, the construction of subcategory classifiers from part classifiers allows us to automatically determine which parts are most relevant when distinguishing between any two subcategories. We can use this to generate illustrations of the differences between subcategories. To demonstrate this, we have built a digital field guide to North American birds which includes automatically generated images highlighting the key differences between visually similar species. This guide, "Birdsnap," also identifies bird species in users' uploaded photos using our subcategory classifiers. We have released Birdsnap as a web site and iPhone application.

Tang Yuk Ming = 電影中三維人面模型之估計 / 鄧育明. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 107-113). / Text in English; abstracts in English and Chinese. / Tang Yuk Ming = Dian ying zhong san wei ren mian mo xing zhi gu ji / Deng Yuming. / Acknowledgement --- p.i / Abstract --- p.ii / Contents --- p.vi / List of Figures --- p.viii / List of Tables --- p.x / List of Abbreviations and Notations --- p.xi / Chapter 1. --- Introduction --- p.1 / Chapter 1.1 --- Introduction --- p.1 / Chapter 1.2 --- Recent Research Works --- p.2 / Chapter 1.2.1 --- Face modeling from images --- p.2 / Chapter 1.2.2 --- Pose estimation --- p.4 / Chapter 1.3 --- Objectives and Assumptions --- p.7 / Chapter 1.4 --- Our Method --- p.8 / Chapter 1.5 --- Thesis Outline --- p.10 / Chapter 2. --- Basic Theory on 3D Modeling of a Head --- p.11 / Chapter 2.1 --- Introduction --- p.11 / Chapter 2.2 --- Perspective Projection --- p.13 / Chapter 2.3 --- Initialization --- p.17 / Chapter 2.3.1 --- Generic wireframe face model and fiducial points --- p.17 / Chapter 2.3.2 --- Deformations --- p.22 / Chapter 2.3.3 --- Experimental results --- p.35 / Chapter 2.4 --- Summary --- p.39 / Chapter 3. --- Pose Estimation --- p.40 / Chapter 3.1 --- Introduction --- p.40 / Chapter 3.2 --- Problem Description --- p.42 / Chapter 3.3 --- Iterative Least-Square Minimization --- p.45 / Chapter 3.3.1 --- Depth estimation --- p.45 / Chapter 3.3.2 --- Least-square minimization --- p.47 / Chapter 3.3.3 --- Iterative process --- p.52 / Chapter 3.4 --- Experimental Results --- p.54 / Chapter 3.4.1 --- Synthetic data --- p.54 / Chapter 3.4.2 --- Real data --- p.65 / Chapter 3.5 --- Summary --- p.69 / Chapter 4. --- 3D Wireframe Model Estimation --- p.70 / Chapter 4.1 --- Introduction --- p.70 / Chapter 4.2 --- 3D Wireframe Model Estimation --- p.72 / Chapter 4.2.1 --- Least-square minimization --- p.73 / Chapter 4.2.2 --- Iterative process --- p.74 / Chapter 4.3 --- 3D Wireframe Model Estimation of the Subsequent Frames --- p.77 / Chapter 4.4 --- Experimental Results --- p.78 / Chapter 4.4.1 --- Synthetic data --- p.78 / Chapter 4.4.2 --- Real data --- p.84 / Chapter 4.5 --- Summary --- p.98 / Chapter 5. --- Contributions and Conclusions --- p.99 / Chapter 5.1 --- Contributions and conclusions --- p.99 / Chapter 5.2 --- Future Developments --- p.102 / Appendix A Triangles and vertices on the IST model --- p.104 / Bibliography --- p.107

The No Child Left Behind Act (2002) and Race to the Top (2009) legislation have forged new school accountability measures and led to a sharp increase in demand for teacher professional development (TPD). However, data revealed that there is a disconnection between the training that teachers receive and its implementation, limiting its impact on student achievement. This qualitative case study's purpose was to reveal major barriers to TPD implementation and provide suggestions for crafting more impactful TPD. Based on the social constructivist foundation, this study sought to address the factors that increase teachers' receptiveness to more effective teaching techniques. It explored middle school teachers' perceptions of TPD, its connection to student achievement, and factors influencing implementation. Semi-structured interviews with open-ended questions helped to identify emergent themes. Nine participants were purposefully selected to gather data from perspectives across race, gender, and various teaching experiences. This study took an inductive approach using the constant comparison methodology of data analysis. Participants identified influencing factors regarding TPD, such as the inclusion of a follow-up component for accountability and feedback. Also, the participants insisted that TPD must be seen as non-punitive, relevant, engaging, and non-hypocritical; for example, a lecture cannot teach teachers about the ineffectiveness of teaching via lecture. These findings encourage positive social change by providing insight into crafting more impactful TPD. Ultimately, improved TPD encourages better teaching methodologies, increased teacher morale, and higher student achievement.

This thesis investigates the relationship between social meaning and linguistic change. An important observation regarding spoken languages is that they are constantly changing: the way we speak differs from generation to generation. A second important observation is that spoken utterances convey social as well as denotational meaning: the way we speak communicates something about who we are. How, if at all, are these two characteristics of spoken languages related? Many sociolinguistic studies have argued that the social meaning of linguistic features is central to explaining the spread of linguistic innovations. A novel form might be heard as more prestigious than the older form, or it may become associated with specific social stereotypes relevant to the community in which the change occurs. It is argued that this association between a linguistic variant and social meaning leads speakers to adopt or reject the innovation, inhibiting or facilitating the spread of the change. In contrast, a number of scholars have argued that social meaning is epiphenomenal to many linguistic changes, which are instead driven by an automatic process of convergence in face-to-face interaction. The issue that such arguments raise is that many studies proposing a role of social meaning in the spread of linguistic innovations rely on production data as their primary source of evidence. Observing the variable adoption of innovations across different groups of speakers (e.g. by gender, ethnicity, or socioeconomic status), a researcher might draw on their knowledge of the social history of the community under study to infer the role of social meaning in that change. In many cases, the observed patterns of could equally be explained by the social structure of the community under study, which constrains who speaks to whom. Are linguistic changes facilitated and inhibited by social meaning? Or is it rather the case that social meaning arises as a consequence of linguistic change, without necessarily influencing the change itself? This thesis explores these questions through a study of vocalic change in York, Northern England, focusing on the fronting and diphthongization of the tense back vowels /u/ and /o/. It presents a systematic comparison of the social meanings listeners assign to innovations (captured using perceptual methods), their social attitudes with regard to those meanings (captured through sociolinguistic interviews), and their use of those forms in production (captured through acoustic analysis). It is argued that evidence of a consistent relationship between these factors would support the proposal that social meaning plays a role in linguistic change. The results of this combined analysis of sociolinguistic perception, social attitudes and speech production provide clear evidence of diachronic /u/ and /o/ fronting in this community, and show that variation in these two vowels is associated with a range of social meanings in perception. These meanings are underpinned by the notion of 'Broad Yorkshire' speech, a socially-recognized speech register linked to notions of authentic local identity and social class. Monophthongal /o/, diphthongal /u/, and back variants of both vowels are shown to be associated with this register, implying that a speaker who adopts an innovative form will likely be heard as less 'Broad'. However, there is no clear evidence that speakers' attitudes toward regional identity or social class have any influence on their adoption of innovations, nor that that their ability to recognise the social meaning of fronting in perception is related to their production behaviour. The fronting of /u/ is spreading in a socially-uniform manner in production, unaffected by any social factor tested except for age. The fronting of /o/ is conditioned by social network structure - speakers with more diverse social networks are more likely to adopt the innovative form, while speakers with closer social ties to York are more likely to retain a back variant. These findings demonstrate that York speakers hear back forms of /u/ and /o/ as more 'local' and 'working class' than fronter realizations, and express strong attitudes toward the values and practices associated with regional identity and social class. However, these factors do not appear to influence their adoption of linguistic innovations in any straightforward manner, contrasting the predictions of an account of linguistic change where social meaning plays a central role in facilitating or inhibiting the propagation of linguistic innovations. Based on these results, the thesis argues that many linguistic changes may spread through the production patterns of a speech community without the direct influence of social meaning, and advocates for the combined analysis of sociolinguistic perception, social attitudes and speech production in future work.