704 resultados para Geometry, Non-Euclidian

em Queensland University of Technology - ePrints Archive


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A robust visual tracking system requires an object appearance model that is able to handle occlusion, pose, and illumination variations in the video stream. This can be difficult to accomplish when the model is trained using only a single image. In this paper, we first propose a tracking approach based on affine subspaces (constructed from several images) which are able to accommodate the abovementioned variations. We use affine subspaces not only to represent the object, but also the candidate areas that the object may occupy. We furthermore propose a novel approach to measure affine subspace-to-subspace distance via the use of non-Euclidean geometry of Grassmann manifolds. The tracking problem is then considered as an inference task in a Markov Chain Monte Carlo framework via particle filtering. Quantitative evaluation on challenging video sequences indicates that the proposed approach obtains considerably better performance than several recent state-of-the-art methods such as Tracking-Learning-Detection and MILtrack.

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Areal bone mineral density (aBMD) is the most common surrogate measurement for assessing the bone strength of the proximal femur associated with osteoporosis. Additional factors, however, contribute to the overall strength of the proximal femur, primarily the anatomical geometry. Finite element analysis (FEA) is an effective and widely used computerbased simulation technique for modeling mechanical loading of various engineering structures, providing predictions of displacement and induced stress distribution due to the applied load. FEA is therefore inherently dependent upon both density and anatomical geometry. FEA may be performed on both three-dimensional and two-dimensional models of the proximal femur derived from radiographic images, from which the mechanical stiffness may be redicted. It is examined whether the outcome measures of two-dimensional FEA, two-dimensional, finite element analysis of X-ray images (FEXI), and three-dimensional FEA computed stiffness of the proximal femur were more sensitive than aBMD to changes in trabecular bone density and femur geometry. It is assumed that if an outcome measure follows known trends with changes in density and geometric parameters, then an increased sensitivity will be indicative of an improved prediction of bone strength. All three outcome measures increased non-linearly with trabecular bone density, increased linearly with cortical shell thickness and neck width, decreased linearly with neck length, and were relatively insensitive to neck-shaft angle. For femoral head radius, aBMD was relatively insensitive, with two-dimensional FEXI and threedimensional FEA demonstrating a non-linear increase and decrease in sensitivity, respectively. For neck anteversion, aBMD decreased non-linearly, whereas both two-dimensional FEXI and three dimensional FEA demonstrated a parabolic-type relationship, with maximum stiffness achieved at an angle of approximately 15o. Multi-parameter analysis showed that all three outcome measures demonstrated their highest sensitivity to a change in cortical thickness. When changes in all input parameters were considered simultaneously, three and twodimensional FEA had statistically equal sensitivities (0.41±0.20 and 0.42±0.16 respectively, p = ns) that were significantly higher than the sensitivity of aBMD (0.24±0.07; p = 0.014 and 0.002 for three-dimensional and two-dimensional FEA respectively). This simulation study suggests that since mechanical integrity and FEA are inherently dependent upon anatomical geometry, FEXI stiffness, being derived from conventional two-dimensional radiographic images, may provide an improvement in the prediction of bone strength of the proximal femur than currently provided by aBMD.

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Spontaneous facial expressions differ from posed ones in appearance, timing and accompanying head movements. Still images cannot provide timing or head movement information directly. However, indirectly the distances between key points on a face extracted from a still image using active shape models can capture some movement and pose changes. This information is superposed on information about non-rigid facial movement that is also part of the expression. Does geometric information improve the discrimination between spontaneous and posed facial expressions arising from discrete emotions? We investigate the performance of a machine vision system for discrimination between posed and spontaneous versions of six basic emotions that uses SIFT appearance based features and FAP geometric features. Experimental results on the NVIE database demonstrate that fusion of geometric information leads only to marginal improvement over appearance features. Using fusion features, surprise is the easiest emotion (83.4% accuracy) to be distinguished, while disgust is the most difficult (76.1%). Our results find different important facial regions between discriminating posed versus spontaneous version of one emotion and classifying the same emotion versus other emotions. The distribution of the selected SIFT features shows that mouth is more important for sadness, while nose is more important for surprise, however, both the nose and mouth are important for disgust, fear, and happiness. Eyebrows, eyes, nose and mouth are important for anger.

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An electropolishing method has been developed for preparing sharp needles from polycrystalline YBa2Cu3O7-δ by modifying a recipe for TEM specimen preparation. The method is characterized by a polishing temperature of below 0°C, a non-acidic electrolyt and an even removal of the constituent phases. An approach was employed of combining I-V measurements for polishing process and microscopical observation of surface morphology in finding optimum polishing conditions. TEM evidenced that no preferential attack appeared to grain boundaries. X-ray diffractometry and electron diffraction implied that no change in oxygen content occurred during electropolishing. The sharpness of the tip was examined by field-ion microscopy.

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This thesis is a study in narratology that examines the pre-theoretical ideas that underlie the study of narrative and time. The thesis explores how the lemniscate can be transported from geometry to narrative in order to structure a non-linear story that breaks the rules of causality and chronology by coupling physical movement through space with the backward pull of memory. The findings offer new possibilities for understanding the nexus between shape and story and for recording non-linear narratives that are marked by simultaneity, counterpoint, and reversal.

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Constrained topography and complex road geometry along rural mountainous roads often represent a demanding driving situation. As a result, traffic crashes along mountainous roads are likely to have different characteristics to crashes on roads in flatter areas; however, there is little research on this topic. The objective of this study is to examine the characteristics of road traffic crashes on rural mountainous roads and to compare these with the characteristics of crashes on non-mountainous roads. This paper explores and compares general crash characteristics including crash type, crash severity, roadway geometric features and environmental factors, and road user/vehicle characteristics. Five years of road traffic crash data (2008-2012) for Sabah were obtained from the Malaysian Institute of Road Safety Research. During this period, a total of 25,439 crashes occurred along federal roads in Sabah, of which 4,875 crashes occurred in mountainous areas. Categorical data analysis techniques were used to examine the differences between mountainous and non-mountainous crashes. Results show that the odds ratio of ‘out-of-control’ crashes and the crash involvement due to speeding are respectively about 4.2 times and 2.8 times higher on mountainous than non-mountainous roads. Other factors and crash characteristics that increase the odds of crashes along mountainous roads compared with non-mountainous roads include horizontal curved sections compared with straight sections, single-vehicle crashes compared with multi-vehicle crashes and weekend crashes compared with weekday crashes. This paper identifies some of the basic characteristics of crashes along rural mountainous roads to aid future research on traffic safety along mountainous roads.

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Constrained topography and complex road geometry along rural mountainous roads often represent a demanding driving situation. As a result, traffic crashes along mountainous roads are likely to have different characteristics to crashes on roads in flatter areas; however, there is little research on this topic. The objective of this study is to examine the characteristics of road traffic crashes on rural mountainous roads and to compare these with the characteristics of crashes on non-mountainous roads. This paper explores and compares general crash characteristics including crash type, crash severity, roadway geometric features and environmental factors, and road user/vehicle characteristics. Five years of road traffic crash data (2008-2012) for Sabah were obtained from the Malaysian Institute of Road Safety Research. During this period, a total of 25,439 crashes occurred along federal roads in Sabah, of which 4,875 crashes occurred in mountainous areas. Categorical data analysis techniques were used to examine the differences between mountainous and non-mountainous crashes. Results show that the odds ratio of ‘out-of-control’ crashes and the crash involvement due to speeding are respectively about 4.2 times and 2.8 times higher on mountainous than non-mountainous roads. Other factors and crash characteristics that increase the odds of crashes along mountainous roads compared with non-mountainous roads include horizontal curved sections compared with straight sections, single-vehicle crashes compared with multi-vehicle crashes and weekend crashes compared with weekday crashes. This paper identifies some of the basic characteristics of crashes along rural mountainous roads to aid future research on traffic safety along mountainous roads.

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Hospital acquired infections (HAI) are costly but many are avoidable. Evaluating prevention programmes requires data on their costs and benefits. Estimating the actual costs of HAI (a measure of the cost savings due to prevention) is difficult as HAI changes cost by extending patient length of stay, yet, length of stay is a major risk factor for HAI. This endogeneity bias can confound attempts to measure accurately the cost of HAI. We propose a two-stage instrumental variables estimation strategy that explicitly controls for the endogeneity between risk of HAI and length of stay. We find that a 10% reduction in ex ante risk of HAI results in an expected savings of £693 ($US 984).

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In this paper, a singularly perturbed ordinary differential equation with non-smooth data is considered. The numerical method is generated by means of a Petrov-Galerkin finite element method with the piecewise-exponential test function and the piecewise-linear trial function. At the discontinuous point of the coefficient, a special technique is used. The method is shown to be first-order accurate and singular perturbation parameter uniform convergence. Finally, numerical results are presented, which are in agreement with theoretical results.