Supporting user designs of 3D contents remains a challenge in geometric modeling. Various modeling tools have been developed in recent years to facilitate architectural designs and artistic creations. However, these tools require both modeling skills and raw creativity. Instead of creating models from scratch, one of the most popular choices is to extract intrinsic patterns from exemplar inputs (e.g., shape collections and sketches), to produce creative models while preserving the patterns. The mod- eling process contains two main stages, analysis and synthesis. The analysis of input models is usually performed at component level, especially for man-made objects that can be decomposed into several semantic parts, for example, the seat and handles of a bicycle. The synthesis stage recombines parts of shapes to generate new models that usually have topological or geometric variations. In this thesis, we propose three design tools aimed at easing the modeling process. We focus on man-made objects and scenes such as buildings and furniture, as the functionality of such shapes can be analyzed at the component level. A relation graph, which is commonly used in shape analysis, can then be built to represent the input shapes. In our work, the graph nodes denote the elements of a model (i.e., rooms, shape parts, and strokes respectively), while the edges capture the intrinsic relations between connected elements. With the use of graph representations, we extract and present controllable components to users for supporting their designs. The emphasis of our work is on three aspects. Firstly, we propose a framework for supporting interior layout design, which allows users to manipulate the produced floor plans, i.e., changing the scales of rooms and their positions as well. When the user modifies the topology of a layout, the corresponding layout graph is updated and the room geometries are optimized under certain constraints, e.g., user specified scales, the adjacency of rooms, and fabrication considerations (i.e., economic construction cost). Secondly, we introduce replaceable substructures as arrangements of shape components that can be interchanged while ensuring boundary consistency. Based on the shape graphs that encode the structures of input models, we propose new automatic operations to discover replaceable substructures across models or within a model. We enforce a pair of subgraphs matching along their boundaries so that switching two subgraphs results in topological variations. Thirdly, we develop an interactive system that supports a freeform design by interpreting user sketches. 3D contents can be extracted from input strokes with or without user annotations. Our system accepts user strokes, analyzes their contacts and vanishing directions with respect to an anchored image, and projects 2D strokes to 3D space via a multi- stage optimization on spatial canvas selection. We demonstrate the computational approaches on a range of example models and design studies.

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The mammalian neocortex is integral to all aspects of cognition, in particular perception across all sensory modalities. Whether computational principles can be identified that would explain why the cortex is so versatile and capable of adapting to various inputs is not clear. One well-known hypothesis is that the cortex implements a generative model, actively synthesising internal explanations of the sensory input. This ‘analysis by synthesis’ could be instantiated in the top-down connections in the hierarchy of cortical regions, and allow the cortex to evaluate its internal model and thus learn good representations of sensory input over time. Few computational models however exist that implement these principles. In this thesis, we investigate the deep Boltzmann machine (DBM) as a model of analysis by synthesis in the cortex, and demonstrate how three distinct perceptual phenomena can be interpreted in this light: visual hallucinations, bistable perception, and object-based attention. A common thread is that in all cases, the internally synthesised explanations go beyond, or deviate from, what is in the visual input. The DBM was recently introduced in machine learning, but combines several properties of interest for biological application. It constitutes a hierarchical generative model and carries both the semantics of a connectionist neural network and a probabilistic model. Thus, we can consider neuronal mechanisms but also (approximate) probabilistic inference, which has been proposed to underlie cortical processing, and contribute to the ongoing discussion concerning probabilistic or Bayesian models of cognition. Concretely, making use of the model’s capability to synthesise internal representations of sensory input, we model complex visual hallucinations resulting from loss of vision in Charles Bonnet syndrome.We demonstrate that homeostatic regulation of neuronal firing could be the underlying cause, reproduce various aspects of the syndrome, and examine a role for the neuromodulator acetylcholine. Next, we relate bistable perception to approximate, sampling-based probabilistic inference, and show how neuronal adaptation can be incorporated by providing a biological interpretation for a recently developed sampling algorithm. Finally, we explore how analysis by synthesis could be related to attentional feedback processing, employing the generative aspect of the DBM to implement a form of object-based attention. We thus present a model that uniquely combines several computational principles (sampling, neural processing, unsupervised learning) and is general enough to uniquely address a range of distinct perceptual phenomena. The connection to machine learning ensures theoretical grounding and practical evaluation of the underlying principles. Our results lend further credence to the hypothesis of a generative model in the brain, and promise fruitful interaction between neuroscience and Deep Learning approaches.

Pateikiama kodavimo-dekodavimo schema, veikianti uždaros kilpos principu, kaip informacinis gyvųjų sistemų funkcinės organizacijos pamatas. Ji pagrįsta teoriniais ir eksperimentiniais tyrimais. Ši kodavimo-dekodavimo schema naudojama sisteminiu ir bioinformatikos požiūriu paaiškinti 1) biogenezę – genotipo ir fenotipo dinaminės dvejybės atsiradimą, 2) žinduolių, ypač žmogaus, smegenų žievės (neocortex) funkcinę organizaciją. Teigiama, kad suvokimo bei mąstymo funkcinis pamatas - analizė per sintezę - yra labiausiai išvystyta gyvųjų sistemų kodavimo-dekodavimo procedūra. Tai ypatinga problemų sprendimo technologija, sugebanti individualiai gaminti informaciją. Pagrindinis dėmesys skiriamas neuronų tinklų funkcinei veiklai aiškinti taikant neurosluoksnių, kurie atlieka daugiamačių (erdvės ir laiko) signalų filtro funkcijas vykdydami integralines transformacijas, sąvoką bei miglotosios (fuzzy) logikos principus – daugiau-mažiau-lygu logiką. Pateikiamas galimas atminties mechanizmų neurochaoso principas bei hipotetinė schema, kaip yra sudarytos regos analizatoriaus neurosluoksninės struktūros, vykdančios kvaziortogonalines vaizdų kodavimo-dekodavimo procedūras, artimas Ermito-Lagero bei kvaziholografinėms transformacijoms. / The concept of closed-loop coding-decoding as the informational principle of funcional organization of living systems is presented. It is based on theory and experimental research. The scheme of coding-decoding is applied to interpret 1) the biogenesis as the dynamic duality of genotype and phenotype, and 2) the functional organization of the mammalian, especialy, human neocortex. It is stated that analysis by synthesis as the functional base of perception and thinking is the most developed coding-decoding procedure of living systems. It is the special technology of problems solving, that is able to produce information individually. The main attention is payed to the interpretation of functioning of the neuronets by the principles of fuzzy logics (more-less-equal logics) and the concept of neurolayers, that function as the multidimensional (space and time) signal filters carrying out the integral transformations. The hypothetic scheme of the functional organization of the neurolayer structures of the visual analyzer is presented. It interprets the quasi-orthogonal procedures similar to Hermite-Lagger transformations, and the quasi-holographic ones. The possible neurochaotic principle of the memory mechanisms is discussed.

Projectively textured models are used in an increasingly large number of applicationsthat dynamically combine images with a simple geometric surface in a viewpoint dependentway. These models can provide visual fidelity while retaining the effects affordedby geometric approximation such as shadow casting and accurate perspective distortion.However, the number of stored views can be quite large and novel views must be synthesizedduring the rendering process because no single view may correctly texture the entireobject surface. This work introduces the Master Texture encoding and demonstrates thatthe encoding increases the utility of projectively textured objects by reducing render-timeoperations. Encoding involves three steps; 1) all image regions that correspond to the samegeometric mesh element are extracted and warped to a facet of uniform size and shape,2) an efficient packing of these facets into a new Master Texture image is computed, and3) the visibility of each pixel in the new Master Texture data is guaranteed using a simplealgorithm to discard occluded pixels in each view. Because the encoding implicitly representsthe multi-view geometry of the multiple images, a single texture mesh is sufficientto render the view-dependent model. More importantly, every Master Texture image cancorrectly texture the entire surface of the object, removing expensive computations suchas visibility analysis from the rendering algorithm. A benefit of this encoding is the supportfor pixel-wise view synthesis. The utility of pixel-wise view synthesis is demonstratedwith a real-time Master Texture encoded VDTM application. Pixel-wise synthesis is alsodemonstrated with an algorithm that distills a set of Master Texture images to a singleview-independent Master Texture image.

This thesis explores communication with children affected by sickle cell disease about their condition from the perspectives of both children and parents. It includes three papers: A literature review, an empirical paper and a critical appraisal. Papers one and two have been prepared for submission to Social Science and Medicine and Qualitative Health Research, respectively. Paper one is a meta-synthesis of qualitative literature investigating experiences of communication from the perspective of children with sickle cell disease. A systematic literature search revealed nine relevant papers, which were synthesised by extracting findings related to communication about sickle cell disease. Children were found to receive inconsistent messages about their condition from different personal and professional groups. Communication about the prognosis of sickle cell disease and the social acceptability of the condition differed across the groups. The implications for children's understandings of their condition and their adjustment are discussed. Paper two presents an empirical study of parental communication experiences with children affected by sickle cell disease. Twelve interviews were conducted and subject to inductive thematic analysis which was applied within a contextualist epistemological framework. Parents described skills in 'coaching' their child to negotiate the various challenges associated with managing sickle cell disease. They also described ways in which they avoided challenging topics of communication such as inheritance, the risk of comorbid disease and the life-long nature of the condition. The findings suggest a need for healthcare professionals to support parents in overcoming barriers to talking about difficult topics. This may facilitate more consistent communication between parents and professionals, which has implications for improving child wellbeing and adjustment. Paper three is a reflective piece and is not intended for publication. It critically evaluates papers one and two and discusses the joint implications of the findings for research and clinical practice. Reflections on the experience of conducting a meta-synthesis and an empirical qualitative study are offered in the context of personal and professional development.

This thesis explores the perspectives of people on psychogenic non-epileptic seizures (PNES). It is presented in three separate papers: a systematic literature review; an empirical research paper and a critical reflection of the research process as a whole. The systematic literature review aimed to provide a detailed understanding of stakeholder perspectives on PNES. A systematic search identified relevant studies that were subsequently synthesised using thematic analysis and the broader principles of narrative synthesis. Three broad themes relating to stakeholder perspectives were identified: the nature of PNES as a condition; diagnosis; and management and treatment issues. It was found that both patients and professionals experienced uncertainties in relation to understanding and managing the condition. This highlighted the need for further information and awareness of PNES and the development of clear treatment guidelines. Important differences in opinion were also identified between patients and professionals and consideration was given to how these may disrupt the development of effective partnerships in care. The research into patients' and families' perspectives was found to be lacking and further research was identified as being needed in this area. The empirical paper reports an exploratory qualitative study that aimed to provide an in-depth understanding of the perceived treatment needs of patients with PNES. Semi-structured interviews were conducted and findings were analysed inductively using the principles of thematic analysis. Four key themes were identified: return to normality; post-diagnostic limbo; uncertainty and apprehension about therapy; and need for validation. Patients with PNES described clear goals for their recovery and clear ideas about their treatment needs. However, following their diagnosis, many felt caught in 'limbo' due to uncertainties about their diagnosis and as a result of a lack of post-diagnostic support. Being in 'limbo' also linked to patients' uncertainties about psychology meeting their needs and for some there was apprehension about the potential negative consequences of therapy. The clinical implications of the research are discussed and recommendations for future research are made. The third paper is a critical reflection of the research process as a whole. It provides an overview and evaluation of the first two papers and personal reflections of the lead researcher are offered throughout. Implications for further research and clinical practice are offered and a summary of the research as a whole is offered.

<div> <div> <div> <p>In this thesis, two aspects of video coding improvement are discussed, namely error resilience and coding efficiency. </p> <p>With the increasing amount of videos being created and consumed, better video compression tools are needed to provide reliable and fast transmission. Many popular video coding standards such as VPx, H.26x achieve video compression by using spa- tial and temporal dependencies in the source video signal. This makes the encoded bitstream vulnerable to errors during transmission. In this thesis, we investigate an error resilient video coding for the VP9 bitstreams using error resilience packets. An error resilient packet consists of encoded keyframe contents and the prediction sig- nals for each non-keyframe. Experimental results exhibit that our proposed method is effective under typical packet loss conditions. </p> <p>In the second part of the thesis, we first present an automatic stillness feature detection method for group of pictures. The encoder adaptively chooses the coding structure for each group of pictures based on its stillness feature to optimize the coding efficiency. </p> <p>Secondly, a content-based video coding method is proposed. Modern video codecs including the newly developed AOM/AV1 utilize hybrid coding techniques to remove spatial and temporal redundancy. However, the efficient exploitation of statistical dependencies measured by a mean squared error (MSE) does not always produce the best psychovisual result. One interesting approach is to only encode visually relevant information and use a different coding method for “perceptually insignificant” regions </p> </div> </div> <div> <div> <p>xiv </p> </div> </div> </div> <div> <div> <div> <p>in the frame. In this thesis, we introduce a texture analyzer before encoding the input sequences to identify detail irrelevant texture regions in the frame using convolutional neural networks. The texture region is then reconstructed based on one set of motion parameters. We show that for many standard test sets, the proposed method achieved significant data rate reductions. </p> </div> </div> </div>

<p dir="ltr">Land cover classification has always been a crucial topic in the remote sensing domain. Utilizing data collected by unmanned aerial vehicles and satellites, researchers can detect land degradation, monitor environmental changes, and provide insights for urban planning. Recent advancements in large multi-modal models have enabled open-vocabulary classification, which is particularly beneficial in this field. Becuase of the pre-training method, these models can perform zero-shot inference on unseen data, significantly reducing the costs associated with data collection and model training. This open-vocabulary feature of large-scale vision-language pre-training aligns well with the requirements of land cover classification, where benchmark datasets in the remote sensing domain comprise various categories, and transferring results from one dataset to another through supervised learning methods is challenging.</p><p dir="ltr">In this thesis, the author explored the performance of zero-shot CLIP and linear probe CLIP to assess the feasibility of using the CLIP model for land cover classification tasks. Further, the author fine-tuned CLIP by creating hierarchical label sets for the datasets, leading to better zero-shot classification results and improving overall accuracy by 2.5%. Regarding data engineering, the author examined the performance of zero-shot CLIP and linear probe CLIP across different categories and proposed a categorization method for land cover datasets. In summary, this work evaluated CLIP's overall performance on land cover datasets of varying spatial resolutions and proposed a hierarchical classification method to enhance its zero-shot performance. The thesis also offers a practical approach for modifying current dataset categorizations to better align with the model.</p>

A expressividade é um elemento chave para o transporte de emoções em música, e seu modelamento, vital para a concepção de sistemas de síntese mais realistas. Gestos musicais executados durante a interpretação usualmente portam a informação responsável pela expressividade percebida, e podem ser rastreados por meio de padrões sônicos a eles associados em diversas escalas de resolução. Um conjunto relevante de gestos musicais expressivos foi estudado através de uma análise em multiresolução utilizando-se a transformada wavelet. A escolha deve-se principalmente à capacidade natural desta ferramenta em realizar análises de tempo-escala/frequência, e suas semelhanças com o processamento dos estágios primários do sistema auditivo. Vinte e sete eventos musicais foram capturados em interpretações de violino e flauta, e analisados com o objetivo de avaliar a aplicabilidade desta ferramenta na identificação e segregação de padrões sônicos associados a gestos musicais expressivos. Os algoritmos wavelet foram implementados na plataforma MATLAB utilizando-se bancos de filtros organizados em esquema piramidal. Rotinas para análises gráfica e sônica e uma interface ao usuário foram também implementadas. Verificou-se que as wavelets permitem a identificação de padrões sônicos associados a gestos expressivos exibindo diferentes propriedades em níveis diferentes da análise. A técnica mostrou-se útil para isolar ruídos oriundos de fontes diversas, extrair transientes associados a gestos súbitos e/ou intensos, e para segregar a estrutura harmônica de tons musicais, entre outras potencialidades não menos importantes. Particularidades da técnica e efeitos secundários observados são discutidos, e os padrões sônicos observados nos níveis wavelets são correlacionados com os gestos musicais que lhes deram origem. São propostos trabalhos futuros objetivando a investigação de certos eventos musicais e fenômenos verificados, bem como o estudo de implementações alternativas. / Expressiveness is a key element for emotion transportation in music, and its modeling necessary to conceive more realistic synthesis systems. Musical gestures executed during a performance carry the information answering for expressiveness, and may be tracked by means of sonic patterns associated to them within several resolution scales. A relevant set of musical gestures was studied through a multiresolution analysis using the wavelet transform. The choice for this tool is mainly due to its natural ability to perform time-scale/frequency analysis, and for its similarities with early auditory processing stages. Twenty seven musical events were captured from violin and flute performances, and analyzed in order to evaluate the applicability of this tool for identification and segregation of sonic patterns associated with expressive musical gestures. The wavelet algorithms were implemented on the MATLAB platform, employing filter banks organized in a pyramidal scheme. Graphical and sonic analysis routines and a user interface were carried out over the same platform. It was verified that wavelets enable the identification of sonic patterns associated to musical gestures revealing different properties on different levels of the analysis. The technique showed up useful to isolate noise from different sources, extract transients associated to sudden and/or intense gestures, and segregate the tonal harmonic structure, among other important features. Particularities of the technique and secondary effects observed are discussed, and sonic patterns on wavelet levels are correlated with the musical gestures which produced them. Future works are proposed addressing further investigation of certain musical events and phenomena observed, as well as the study of alternative implementations.