395 resultados para Binary Image Representation


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In the field of face recognition, Sparse Representation (SR) has received considerable attention during the past few years. Most of the relevant literature focuses on holistic descriptors in closed-set identification applications. The underlying assumption in SR-based methods is that each class in the gallery has sufficient samples and the query lies on the subspace spanned by the gallery of the same class. Unfortunately, such assumption is easily violated in the more challenging face verification scenario, where an algorithm is required to determine if two faces (where one or both have not been seen before) belong to the same person. In this paper, we first discuss why previous attempts with SR might not be applicable to verification problems. We then propose an alternative approach to face verification via SR. Specifically, we propose to use explicit SR encoding on local image patches rather than the entire face. The obtained sparse signals are pooled via averaging to form multiple region descriptors, which are then concatenated to form an overall face descriptor. Due to the deliberate loss spatial relations within each region (caused by averaging), the resulting descriptor is robust to misalignment & various image deformations. Within the proposed framework, we evaluate several SR encoding techniques: l1-minimisation, Sparse Autoencoder Neural Network (SANN), and an implicit probabilistic technique based on Gaussian Mixture Models. Thorough experiments on AR, FERET, exYaleB, BANCA and ChokePoint datasets show that the proposed local SR approach obtains considerably better and more robust performance than several previous state-of-the-art holistic SR methods, in both verification and closed-set identification problems. The experiments also show that l1-minimisation based encoding has a considerably higher computational than the other techniques, but leads to higher recognition rates.

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Articular cartilage is a complex structure with an architecture in which fluid-swollen proteoglycans constrained within a 3D network of collagen fibrils. Because of the complexity of the cartilage structure, the relationship between its mechanical behaviours at the macroscale level and its components at the micro-scale level are not completely understood. The research objective in this thesis is to create a new model of articular cartilage that can be used to simulate and obtain insight into the micro-macro-interaction and mechanisms underlying its mechanical responses during physiological function. The new model of articular cartilage has two characteristics, namely: i) not use fibre-reinforced composite material idealization ii) Provide a framework for that it does probing the micro mechanism of the fluid-solid interaction underlying the deformation of articular cartilage using simple rules of repartition instead of constitutive / physical laws and intuitive curve-fitting. Even though there are various microstructural and mechanical behaviours that can be studied, the scope of this thesis is limited to osmotic pressure formation and distribution and their influence on cartilage fluid diffusion and percolation, which in turn governs the deformation of the compression-loaded tissue. The study can be divided into two stages. In the first stage, the distributions and concentrations of proteoglycans, collagen and water were investigated using histological protocols. Based on this, the structure of cartilage was conceptualised as microscopic osmotic units that consist of these constituents that were distributed according to histological results. These units were repeated three-dimensionally to form the structural model of articular cartilage. In the second stage, cellular automata were incorporated into the resulting matrix (lattice) to simulate the osmotic pressure of the fluid and the movement of water within and out of the matrix; following the osmotic pressure gradient in accordance with the chosen rule of repartition of the pressure. The outcome of this study is the new model of articular cartilage that can be used to simulate and study the micromechanical behaviours of cartilage under different conditions of health and loading. These behaviours are illuminated at the microscale level using the socalled neighbourhood rules developed in the thesis in accordance with the typical requirements of cellular automata modelling. Using these rules and relevant Boundary Conditions to simulate pressure distribution and related fluid motion produced significant results that provided the following insight into the relationships between osmotic pressure gradient and associated fluid micromovement, and the deformation of the matrix. For example, it could be concluded that: 1. It is possible to model articular cartilage with the agent-based model of cellular automata and the Margolus neighbourhood rule. 2. The concept of 3D inter connected osmotic units is a viable structural model for the extracellular matrix of articular cartilage. 3. Different rules of osmotic pressure advection lead to different patterns of deformation in the cartilage matrix, enabling an insight into how this micromechanism influences macromechanical deformation. 4. When features such as transition coefficient were changed, permeability (representing change) is altered due to the change in concentrations of collagen, proteoglycans (i.e. degenerative conditions), the deformation process is impacted. 5. The boundary conditions also influence the relationship between osmotic pressure gradient and fluid movement at the micro-scale level. The outcomes are important to cartilage research since we can use these to study the microscale damage in the cartilage matrix. From this, we are able to monitor related diseases and their progression leading to potential insight into drug-cartilage interaction for treatment. This innovative model is an incremental progress on attempts at creating further computational modelling approaches to cartilage research and other fluid-saturated tissues and material systems.

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Since the first destination image studies were published in the early 1970s, the field has become one of the most popular in the tourism literature. While reviews of the destination image literature show no commonly agreed conceptualisation of the construct, researchers have predominantly used structured questionnaires for measurement. There has been criticism that the way some of these scales have been selected means a greater likelihood of attributes being irrelevant to participants. This opens up the risk of stimulating uninformed responses. The issue of uninformed response was first raised as a source of error 60 years ago. However, there has been little, if any, discussion in relation to destination image measurement, studies of which often require participants to provide opinion-driven rather than fact-based responses. This paper reports the trial of a ‘don’t know’ (DK) non-response option for participants in two destination image questionnaires. It is suggested the use of a DK option provides participants with an alternative to i) skipping the question, ii) using the scale midpoint to denote neutrality, or iii) providing an uninformed response. High levels of DK usage by participants can then alert the marketer of the need to improve awareness of destination performance for potential salient attributes.

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This thesis examines online spoof videos in China. It shows the relationship between user-created content and change and how such videos are impacting on social memory. In the West, we are witnessing two outstanding trends in media. On the one hand, media are turning more "demotic" (Turner, 2006) and "participatory" (Jenkins, 2006), whereby lay audiences use popular media for identity formation, representation and association, reconfiguring the media and cultural landscape, and rendering invalid the old paradigm based on the dichotomy of audience and author, creator and consumer, expert and amateur. On the other hand, in both mainstream media and user-creation online there is a trend towards "silly citizenship", with comedy, send-ups and spoofs that used to reside in the margin propelled to the central stage in both pleasure and politics (Hartley, 2010), as is shown in the rising popularity of the Daily Show, Colbert Report, and spoof videos in elections ,e.g. the 2008 presidential election in US (Gray, Jones, & Thompson, 2009; Tryon, 2008). User generated content—and spoof subcultures—is now much a debated phenomenon in China. However, with different political (one party rule and censorship) and cultural (media regarded mainly as instrument for education and social stabilization instead of a critical fourth estate) configurations, will the social and cultural impacts of the two trends in the West be as the same in China? If not, what will be the specificities in the China context? The project starts with a historical review of popular culture and user-created content in China, before turning to spoof videos and looking at how they are produced and shared, travel and diffused on the Internet, and how the communities and sub-cultures forming and emerging around spoof videos are changing the overall cultural landscape in China. By acting as a participant observer in online video sharing sites and conducting face-to face as well as online interviews, I identify lead users and creators of spoof videos and the social networks emerging around them. I call these lead users "skill hubs" and their networks "liquid communities", foregrounding the fact that their appeal doesn’t come from their amicable personality, but rather from their creative skills; and that the networks surrounding them are in a permanent flux, with members coming and going as they see fit. I argue that the "liquidness" (Bauman, 2000) of these communities is what makes them constantly creative and appealing. Textual analysis of online videos, their comments and derivatives are conducted to tease out the uses that that can be made of spoof videos, namely as phatic communication, as alternative memory and as political engagement. Through these analyses I show that spoof videos constitute not only a space where young generations can engage with each other, communicate their anger and dissatisfaction, fun and hope, and where they participate in socio-cultural and political debates, but also create a space where they can experiment with their new skills, new ideas, and new citizenship. The rise of spoof videos heralds the beginning of a trend in popular culture in contemporary China towards the "canonization of the jester" and the dethroning of the establishment. I also argue that a historical perspective is needed to understand the current surge of use creativity and user activism in China, and that many forms of popular media we experience today have their antecedents in various stages of Chinese history. The entrenched "control-resistance" binary is inadequate in interpreting the rich, flux and multilayered Internet space in China.

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Information retrieval (IR) by clinicians in the healthcare setting is critical for informing clinical decision-making. However, a large part of this information is in the form of free-text and inhibits clinical decision support and effective healthcare services. This makes meaningful use of clinical free-­text in electronic health records (EHRs) for patient care a difficult task. Within the context of IR, given a repository of free-­text clinical reports, one might want to retrieve and analyse data for patients who have a known clinical finding.

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An optical system which performs the multiplication of binary numbers is described and proof-of-principle experiments are performed. The simultaneous generation of all partial products, optical regrouping of bit products, and optical carry look-ahead addition are novel features of the proposed scheme which takes advantage of the parallel operations capability of optical computers. The proposed processor uses liquid crystal light valves (LCLVs). By space-sharing the LCLVs one such system could function as an array of multipliers. Together with the optical carry look-ahead adders described, this would constitute an optical matrix-vector multiplier.

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The overrepresentation of students from minority ethnic groups in separate special education settings has been extensively documented in North America, yet little research exists for Australian school systems. To address this gap, we systematically analyzed 13 years of enrolment data from the state of New South Wales. Stark differences are seen in patterns of enrolment between Indigenous students, students from a Language Background Other than English (LBOTE), and non-Indigenous English speaking students. Moreover, these differences are increasing. While enrollments of Indigenous students in separate settings increased faster across time than did enrollments of Indigenous students in mainstream, enrollments of LBOTE students in mainstream increased faster than did enrollments of LBOTE students in separate settings.

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The rank and census are two filters based on order statistics which have been applied to the image matching problem for stereo pairs. Advantages of these filters include their robustness to radiometric distortion and small amounts of random noise, and their amenability to hardware implementation. In this paper, a new matching algorithm is presented, which provides an overall framework for matching, and is used to compare the rank and census techniques with standard matching metrics. The algorithm was tested using both real stereo pairs and a synthetic pair with ground truth. The rank and census filters were shown to significantly improve performance in the case of radiometric distortion. In all cases, the results obtained were comparable to, if not better than, those obtained using standard matching metrics. Furthermore, the rank and census have the additional advantage that their computational overhead is less than these metrics. For all techniques tested, the difference between the results obtained for the synthetic stereo pair, and the ground truth results was small.

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“Supermassive” is a synchronised four-channel video installation with sound. Each video channel shows a different camera view of an animated three-dimensional scene, which visually references galactic or astral imagery. This scene is comprised of forty-four separate clusters of slowly orbiting white text. Each cluster refers to a different topic that has been sourced online. The topics are diverse with recurring subjects relating to spirituality, science, popular culture, food and experiences of contemporary urban life. The slow movements of the text and camera views are reinforced through a rhythmic, contemplative soundtrack. As an immersive installation, “Supermassive” operates somewhere between a meditational mind map and a representation of a contemporary data stream. “Supermassive” contributes to studies in the field of contemporary art. It is particularly concerned with the ways that graphic representations of language can operate in the exploration of contemporary lived experiences, whether actual or virtual. Artists such as Ed Ruscha and Christopher Wool have long explored the emotive and psychological potentials of graphic text. Other artists such as Doug Aitken and Pipilotti Rist have engaged with the physical and spatial potentials of audio-visual installations to create emotive and symbolic experiences for their audiences. Using a practice-led research methodology, “Supermassive” extends these creative inquiries. By creating a reflective atmosphere in which divergent textual subjects are pictured together, the work explores not only how we navigate information, but also how such navigations inform understandings of our physical and psychological realities. “Supermassive” has been exhibited internationally at LA Louver Gallery, Venice, California in 2013 and nationally with GBK as part of Art Month Sydney, also in 2013. It has been critically reviewed in The Los Angeles Times.

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We applied a texture-based flow visualisation technique to a numerical hydrodynamic model of the Pumicestone Passage in southeast Queensland, Australia. The quality of the visualisations using our flow visualisation tool, are compared with animations generated using more traditional drogue release plot and velocity contour and vector techniques. The texture-based method is found to be far more effective in visualising advective flow within the model domain. In some instances, it also makes it easier for the researcher to identify specific hydrodynamic features within the complex flow regimes of this shallow tidal barrier estuary as compared with the direct and geometric based methods.

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Concern that poor image of UK construction industry is restricting recruitment has lead to call for action. This paper gives the results of a recent comparative analysis of the image of both UK and Hungarian industries which indicates the UK image to be relatively good. The perceived cause of Hungarian problems is the poor level of organisation and management.

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This paper presents an Image Based Visual Servo control design for Fixed Wing Unmanned Aerial Vehicles tracking locally linear infrastructure in the presence of wind using a body fixed imaging sensor. Visual servoing offers improved data collection by posing the tracking task as one of controlling a feature as viewed by the inspection sensor, although is complicated by the introduction of wind as aircraft heading and course angle no longer align. In this work it is shown that the effects of wind alter the desired line angle required for continuous tracking to equal the wind correction angle as would be calculated to set a desired course. A control solution is then sort by linearizing the interaction matrix about the new feature pose such that kinematics of the feature can be augmented with the lateral dynamics of the aircraft, from which a state feedback control design is developed. Simulation results are presented comparing no compensation, integral control and the proposed controller using the wind correction angle, followed by an assessment of response to atmospheric disturbances in the form of turbulence and wind gusts

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Abstract: Texture enhancement is an important component of image processing, with extensive application in science and engineering. The quality of medical images, quantified using the texture of the images, plays a significant role in the routine diagnosis performed by medical practitioners. Previously, image texture enhancement was performed using classical integral order differential mask operators. Recently, first order fractional differential operators were implemented to enhance images. Experiments conclude that the use of the fractional differential not only maintains the low frequency contour features in the smooth areas of the image, but also nonlinearly enhances edges and textures corresponding to high-frequency image components. However, whilst these methods perform well in particular cases, they are not routinely useful across all applications. To this end, we applied the second order Riesz fractional differential operator to improve upon existing approaches of texture enhancement. Compared with the classical integral order differential mask operators and other fractional differential operators, our new algorithms provide higher signal to noise values, which leads to superior image quality.

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The building sector is the dominant consumer of energy and therefore a major contributor to anthropomorphic climate change. The rapid generation of photorealistic, 3D environment models with incorporated surface temperature data has the potential to improve thermographic monitoring of building energy efficiency. In pursuit of this goal, we propose a system which combines a range sensor with a thermal-infrared camera. Our proposed system can generate dense 3D models of environments with both appearance and temperature information, and is the first such system to be developed using a low-cost RGB-D camera. The proposed pipeline processes depth maps successively, forming an ongoing pose estimate of the depth camera and optimizing a voxel occupancy map. Voxels are assigned 4 channels representing estimates of their true RGB and thermal-infrared intensity values. Poses corresponding to each RGB and thermal-infrared image are estimated through a combination of timestamp-based interpolation and a pre-determined knowledge of the extrinsic calibration of the system. Raycasting is then used to color the voxels to represent both visual appearance using RGB, and an estimate of the surface temperature. The output of the system is a dense 3D model which can simultaneously represent both RGB and thermal-infrared data using one of two alternative representation schemes. Experimental results demonstrate that the system is capable of accurately mapping difficult environments, even in complete darkness.