888 resultados para Ambiguous images


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In this thesis we study the general problem of reconstructing a function, defined on a finite lattice from a set of incomplete, noisy and/or ambiguous observations. The goal of this work is to demonstrate the generality and practical value of a probabilistic (in particular, Bayesian) approach to this problem, particularly in the context of Computer Vision. In this approach, the prior knowledge about the solution is expressed in the form of a Gibbsian probability distribution on the space of all possible functions, so that the reconstruction task is formulated as an estimation problem. Our main contributions are the following: (1) We introduce the use of specific error criteria for the design of the optimal Bayesian estimators for several classes of problems, and propose a general (Monte Carlo) procedure for approximating them. This new approach leads to a substantial improvement over the existing schemes, both regarding the quality of the results (particularly for low signal to noise ratios) and the computational efficiency. (2) We apply the Bayesian appraoch to the solution of several problems, some of which are formulated and solved in these terms for the first time. Specifically, these applications are: teh reconstruction of piecewise constant surfaces from sparse and noisy observationsl; the reconstruction of depth from stereoscopic pairs of images and the formation of perceptual clusters. (3) For each one of these applications, we develop fast, deterministic algorithms that approximate the optimal estimators, and illustrate their performance on both synthetic and real data. (4) We propose a new method, based on the analysis of the residual process, for estimating the parameters of the probabilistic models directly from the noisy observations. This scheme leads to an algorithm, which has no free parameters, for the restoration of piecewise uniform images. (5) We analyze the implementation of the algorithms that we develop in non-conventional hardware, such as massively parallel digital machines, and analog and hybrid networks.

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The problem of detecting intensity changes in images is canonical in vision. Edge detection operators are typically designed to optimally estimate first or second derivative over some (usually small) support. Other criteria such as output signal to noise ratio or bandwidth have also been argued for. This thesis is an attempt to formulate a set of edge detection criteria that capture as directly as possible the desirable properties of an edge operator. Variational techniques are used to find a solution over the space of all linear shift invariant operators. The first criterion is that the detector have low probability of error i.e. failing to mark edges or falsely marking non-edges. The second is that the marked points should be as close as possible to the centre of the true edge. The third criterion is that there should be low probability of more than one response to a single edge. The technique is used to find optimal operators for step edges and for extended impulse profiles (ridges or valleys in two dimensions). The extension of the one dimensional operators to two dimentions is then discussed. The result is a set of operators of varying width, length and orientation. The problem of combining these outputs into a single description is discussed, and a set of heuristics for the integration are given.

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Is an interactive new media art installation that explores how the sharing of images, normally hidden on mobile phones, can reveal more about people's sense of place and this ultimately shared experience. Traditional views on sense of place, as exemplified by Wagner (1972) and Relph (1976), characterise the experience as a fusion of meaning, act and context. Indeed, Relph suggests that it is not just the identity of a place that is important, but also the identity that a person or group has with that place, in particular whether they are experiencing it as an ‘insider’ or ‘outsider’. This work stimulates debate concerning the impact of technology on sense of place. Technology offers a number of bridges between the real and virtual worlds, but in so doing places an increased tension on the sense of place and subsequently the identity of the individual. This, coupled with the increased use of camera phones, has enabled the documentation of all aspects of our lives, the things we do, the objects we encounter and the places we inhabit. The installation taps into these hidden electronic resources by letting people share their sense of place associated with a large scale event. The work explores the changing nature of the sense of place of performers, visitors and residents over the duration of the event. Interaction with the installation will transform the viewer into performer, echoing Relph’s insider-outsider dichotomy

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The Edinburgh Festival Fringe (The Fringe) is the largest arts festival in the world and it has inspired the creation of similar festivals world-wide. Since its conception in 1947, the Fringe has demonstrated significant growth in visitor numbers; ticket sales; and its economic contribution. Despite this, the sustainable future of Edinburgh’s festivals is debated as Edinburgh, ‘the Festival City’, faces threats from other festival destinations. Festivals position Edinburgh creatively in contrast to the city’s traditionally perceived image as a cultural-historic centre. Despite this, little research has been undertaken into the creative and cultural significance of Edinburgh’s festivals, including the Fringe. This interdisciplinary research grounded in marketing, tourism, and festival and event management; and underpinned by constructivism, presents an understanding of types of brand relationships that exist between the Fringe and its primary stakeholders. This is achieved through defining both the Fringe brand image and its primary stakeholders; and applying these definitions to the development of a typology of Fringe-stakeholders’ brand relationships. The significance of this study is evident within its topic of inquiry and the research methods applied. In the little-considered arena of arts festivals and their stakeholders, this is the first in-depth study into the Fringe as a festival and festival brand. Within this, the definition of a Fringe brand image contributes to understanding the cultural and creative significance of the Fringe. Furthermore, this research contributes a unique understanding of the types of stakeholders that are engaged with the Fringe. The types of brand relationships that exist between these stakeholders and the Fringe are another significant contribution to knowledge and understanding. While specific to the present context, these findings may prove transferable to further festivals or events, and related areas and industries. The contribution made by this research to the methodological developments in festival and event studies is of additional significance. The application of visual research methods, including semiotic analysis and photo-elicitation within phenomenological interviews, has previously been applied in marketing, consumer, and tourism research, but not to the understanding of festival brands and stakeholders’ brand relationship types. Findings of this research illustrate that existing marketing and consumer brand frameworks and stakeholder theories are applicable to festivals. Further, it is possible to define ‘a’ Fringe brand image which is subjective and contradictory. The unique open-access and organic, operational model of the Fringe facilitates its many contributors, and consumers. Fringe stakeholders may be categorised according to their level of engagement with the Fringe (as primary or secondary) and their particular stakeholder role(s), which are varied and multiple. Fringe-stakeholder brand relationship types are overwhelmingly positive; and are based upon interpersonal relationship dimensions (including friendships, marriages, kinships and partnerships). Fringe-stakeholder brand relationship types can be classified therefore as having similar dimensions to those brand relationship types previously described for consumer products and brands.

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Morgan, Huw, Habbal, S.R., Woo, R., (2006) 'The Depiction of Coronal Structure in White-Light Images', Solar Physics 236(2) pp.263-272 RAE2008

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R. Zwiggelaar, S.M. Astley, C.J. Taylor and C.R.M. Boggis, 'Linear structures in mammographic images: detection and classification', IEEE Transaction on Medical Imaging 23 (9), 1077-1086 (2004)

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Williams, Mike, 'Words, Images, Enemies: Securitization and International Politics', International Studies Quarterly (2003) 47(4) pp.511-531 RAE2008

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Families of missing people are often understood as inhabiting a particular space of ambiguity, captured in the phrase ‘living in limbo’ (Holmes, 2008). To explore this uncertain ground, we interviewed 25 family members to consider how human absence is acted upon and not just felt within this space ‘in between’ grief and loss (Wayland, 2007). In the paper, we represent families as active agents in spatial stories of ‘living in limbo’, and we provide insights into the diverse strategies of search/ing (technical, physical and emotional) in which they engage to locate either their missing member or news of them. Responses to absence are shown to be intimately bound up with unstable spatial knowledges of the missing person and emotional actions that are subject to change over time. We suggest that practices of search are not just locative actions, but act as transformative processes providing insights into how families inhabit emotional dynamism and transition in response to the on-going ‘missing situation’ and ambiguous loss (Boss, 1999, 2013).

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Wydział Neofilologii: Instytut Filologii Romańskiej

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The purpose of the project is to research the shape and influence of religion and spirituality in the lives of U.S. adolescents; to identify effective practices in the religious, moral, and social formation of the lives of youth; to describe the extent to which youth participate in and benefit from the programs and opportunities that religious communities are offering to their youth; and to foster an informed national discussion about the influence of religion in youth's lives, in order to encourage sustained reflection about and rethinking of our cultural and institutional practices with regard to youth and religion.

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Material discrimination based on conventional or dual energy X-ray computed tomography (CT) imaging can be ambiguous. X-ray diffraction imaging (XDI) can be used to construct diffraction profiles of objects, providing new molecular signature information that can be used to characterize the presence of specific materials. Combining X-ray CT and diffraction imaging can lead to enhanced detection and identification of explosives in luggage screening. In this work we are investigating techniques for joint reconstruction of CT absorption and X-ray diffraction profile images of objects to achieve improved image quality and enhanced material classification. The initial results have been validated via simulation of X-ray absorption and coherent scattering in 2 dimensions.

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A probabilistic, nonlinear supervised learning model is proposed: the Specialized Mappings Architecture (SMA). The SMA employs a set of several forward mapping functions that are estimated automatically from training data. Each specialized function maps certain domains of the input space (e.g., image features) onto the output space (e.g., articulated body parameters). The SMA can model ambiguous, one-to-many mappings that may yield multiple valid output hypotheses. Once learned, the mapping functions generate a set of output hypotheses for a given input via a statistical inference procedure. The SMA inference procedure incorporates an inverse mapping or feedback function in evaluating the likelihood of each of the hypothesis. Possible feedback functions include computer graphics rendering routines that can generate images for given hypotheses. The SMA employs a variant of the Expectation-Maximization algorithm for simultaneous learning of the specialized domains along with the mapping functions, and approximate strategies for inference. The framework is demonstrated in a computer vision system that can estimate the articulated pose parameters of a human’s body or hands, given silhouettes from a single image. The accuracy and stability of the SMA are also tested using synthetic images of human bodies and hands, where ground truth is known.

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A novel method for 3D head tracking in the presence of large head rotations and facial expression changes is described. Tracking is formulated in terms of color image registration in the texture map of a 3D surface model. Model appearance is recursively updated via image mosaicking in the texture map as the head orientation varies. The resulting dynamic texture map provides a stabilized view of the face that can be used as input to many existing 2D techniques for face recognition, facial expressions analysis, lip reading, and eye tracking. Parameters are estimated via a robust minimization procedure; this provides robustness to occlusions, wrinkles, shadows, and specular highlights. The system was tested on a variety of sequences taken with low quality, uncalibrated video cameras. Experimental results are reported.

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The need for the ability to cluster unknown data to better understand its relationship to know data is prevalent throughout science. Besides a better understanding of the data itself or learning about a new unknown object, cluster analysis can help with processing data, data standardization, and outlier detection. Most clustering algorithms are based on known features or expectations, such as the popular partition based, hierarchical, density-based, grid based, and model based algorithms. The choice of algorithm depends on many factors, including the type of data and the reason for clustering, nearly all rely on some known properties of the data being analyzed. Recently, Li et al. proposed a new universal similarity metric, this metric needs no prior knowledge about the object. Their similarity metric is based on the Kolmogorov Complexity of objects, the objects minimal description. While the Kolmogorov Complexity of an object is not computable, in "Clustering by Compression," Cilibrasi and Vitanyi use common compression algorithms to approximate the universal similarity metric and cluster objects with high success. Unfortunately, clustering using compression does not trivially extend to higher dimensions. Here we outline a method to adapt their procedure to images. We test these techniques on images of letters of the alphabet.

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This study develops a neuromorphic model of human lightness perception that is inspired by how the mammalian visual system is designed for this function. It is known that biological visual representations can adapt to a billion-fold change in luminance. How such a system determines absolute lightness under varying illumination conditions to generate a consistent interpretation of surface lightness remains an unsolved problem. Such a process, called "anchoring" of lightness, has properties including articulation, insulation, configuration, and area effects. The model quantitatively simulates such psychophysical lightness data, as well as other data such as discounting the illuminant, the double brilliant illusion, and lightness constancy and contrast effects. The model retina embodies gain control at retinal photoreceptors, and spatial contrast adaptation at the negative feedback circuit between mechanisms that model the inner segment of photoreceptors and interacting horizontal cells. The model can thereby adjust its sensitivity to input intensities ranging from dim moonlight to dazzling sunlight. A new anchoring mechanism, called the Blurred-Highest-Luminance-As-White (BHLAW) rule, helps simulate how surface lightness becomes sensitive to the spatial scale of objects in a scene. The model is also able to process natural color images under variable lighting conditions, and is compared with the popular RETINEX model.