977 resultados para SCENE ANALYSIS
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“A Narratological Analysis of D. M. Thomas’s The White Hotel (1981)” originated within a seminar on British Postmodernist Literature during the first Master’s Degree in “British and North-American Culture and Literature” (2001-04) at the Universidade da Madeira set up by the Department of English and German Studies. This dissertation seeks to present a narratological analysis of Thomas’s novel. The White Hotel stands as a paradigmatic example of the kind of literature that has dominated the British literary scene in the past three decades, commonly referred to as postmodernist fiction, owing to its formal craftsmanship (multiplicity of narrative voices and perspectives, mixing of differing genres and text types, inclusion of embedded narratives) alongside the handling of what are deemed as postmodernist topoi (the distinction between truth and lies, history and fantasy, fact and fiction, the questioning of the nature of aesthetic representation, the role the author and the reader hold in the narrative process, the instability of the linguistic sign, the notion of originality and the moral responsibility the author has towards his/her work), The narratological approach carried out in this research reveals that Thomas’s text constitutes an aesthetic endeavour to challenge the teleological drive that is inherent in any narrative, i. e., the inevitable progression towards a reassuring end. Hence, the subversion of narrative telling, which is a recurrent feature in Thomas’s remaining literary output, mirrors the contemporary distrust in totalising, hierarchised and allencompassing narratives. In its handling of historical events, namely of the Holocaust, The White Hotel invites us to reassess the most profound beliefs we were taught to take for granted: progress, reality and truth. In their place the novel proposes a more flexible conception of both the world and art, especially of literary fiction. In other terms, the world appears as a brutal chaotic place the subject is forced to adjust to. Accordingly, the literary work is deemed hybrid, fragmented and open. So as to put forth the above-mentioned issues, this research work is structured in three main chapters. The initial chapter – “What is Postmodernism?” – advances a scrutiny not only of the seminal but also of more recent studies on postmodernist literary criticism. Following this, in Chapter II – “Postmodernist British Fiction” – a brief overview of postmodernist British fiction is carried out, focusing on the fictional works that, in my opinion, are fundamental for the periodising of British postmodernism. In addition, I felt the need to include a section – “D. M. Thomas as a Postmodernist Novelist” – in which the author’s remaining literary output is briefly examined. Finally, Chapter III – “A Narratological Analysis of The White Hotel” – proposes a narratological analysis of the novel according to the particular Genettian analytical model. To conclude, my dissertation constitutes an approach to D. M. Thomas’s The White Hotel as a text whose very existence is substantiated in the foregrounding of the contingency of all discourses, meeting the postmodernist precepts of openness and subversion of any narrative that claims to be true, globalising and all-inclusive.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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A deep theoretical analysis of the graph cut image segmentation framework presented in this paper simultaneously translates into important contributions in several directions. The most important practical contribution of this work is a full theoretical description, and implementation, of a novel powerful segmentation algorithm, GC(max). The output of GC(max) coincides with a version of a segmentation algorithm known as Iterative Relative Fuzzy Connectedness, IRFC. However, GC(max) is considerably faster than the classic IRFC algorithm, which we prove theoretically and show experimentally. Specifically, we prove that, in the worst case scenario, the GC(max) algorithm runs in linear time with respect to the variable M=|C|+|Z|, where |C| is the image scene size and |Z| is the size of the allowable range, Z, of the associated weight/affinity function. For most implementations, Z is identical to the set of allowable image intensity values, and its size can be treated as small with respect to |C|, meaning that O(M)=O(|C|). In such a situation, GC(max) runs in linear time with respect to the image size |C|. We show that the output of GC(max) constitutes a solution of a graph cut energy minimization problem, in which the energy is defined as the a"" (a) norm ayenF (P) ayen(a) of the map F (P) that associates, with every element e from the boundary of an object P, its weight w(e). This formulation brings IRFC algorithms to the realm of the graph cut energy minimizers, with energy functions ayenF (P) ayen (q) for qa[1,a]. Of these, the best known minimization problem is for the energy ayenF (P) ayen(1), which is solved by the classic min-cut/max-flow algorithm, referred to often as the Graph Cut algorithm. We notice that a minimization problem for ayenF (P) ayen (q) , qa[1,a), is identical to that for ayenF (P) ayen(1), when the original weight function w is replaced by w (q) . Thus, any algorithm GC(sum) solving the ayenF (P) ayen(1) minimization problem, solves also one for ayenF (P) ayen (q) with qa[1,a), so just two algorithms, GC(sum) and GC(max), are enough to solve all ayenF (P) ayen (q) -minimization problems. We also show that, for any fixed weight assignment, the solutions of the ayenF (P) ayen (q) -minimization problems converge to a solution of the ayenF (P) ayen(a)-minimization problem (ayenF (P) ayen(a)=lim (q -> a)ayenF (P) ayen (q) is not enough to deduce that). An experimental comparison of the performance of GC(max) and GC(sum) algorithms is included. This concentrates on comparing the actual (as opposed to provable worst scenario) algorithms' running time, as well as the influence of the choice of the seeds on the output.
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The present thesis aims at proving the importance of cultural and literary contexts in the practice of translation: I shall show that, in the case of Northern Irish crime fiction, knowledge of both Northern Irish history and culture as well as of the genre of crime fiction are essential prerequisites for the production of a “responsible” translation. I will therefore offer a brief overview of the history of crime and detective fiction and its main subgenres; some of the most important authors and works will be presented as well, in an analysis that goes from the early years of the genre to the second half of the 20th century. I will then move the focus to Northern Ireland, its culture and its history, and particular attention will be paid to fiction writing in Ireland and Northern Ireland, with a focus on the peculiar phenomenon of “Troubles Trash”. I will tackle the topic of Northern Irish literature and present the contemporary scene of Northern Irish crime fiction; the volume from which the texts for the translation have been taken will be presented, namely Belfast Noir. Subsequently the focus will move on the theoretical framework within which the translations were produced: I will present a literary review of the most significative developments in Translation Studies, with particular attention to the “cultural turn” that has characterised this subject since the 1960s. I will then highlight the phenomenon of “realia” in translation and analyse the approaches of different scholars to the translation of culture-bound references. The final part represents the culmination and practical application of all that was presented in the previous sections: I will discuss the translation of culture-bound references according to the strategies presented in Chapter 4, referring to the proposed translations of two stories. Such analysis aims to show that not only expert linguistic knowledge, but also cultural awareness and a wide literary background are needed in order to make conscious choices in translation.
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For crime scene investigation in cases of homicide, the pattern of bloodstains at the incident site is of critical importance. The morphology of the bloodstain pattern serves to determine the approximate blood source locations, the minimum number of blows and the positioning of the victim. In the present work, the benefits of the three-dimensional bloodstain pattern analysis, including the ballistic approximation of the trajectories of the blood drops, will be demonstrated using two illustrative cases. The crime scenes were documented in 3D, using the non-contact methods digital photogrammetry, tachymetry and laser scanning. Accurate, true-to-scale 3D models of the crime scenes, including the bloodstain pattern and the traces, were created. For the determination of the areas of origin of the bloodstain pattern, the trajectories of up to 200 well-defined bloodstains were analysed in CAD and photogrammetry software. The ballistic determination of the trajectories was performed using ballistics software. The advantages of this method are the short preparation time on site, the non-contact measurement of the bloodstains and the high accuracy of the bloodstain analysis. It should be expected that this method delivers accurate results regarding the number and position of the areas of origin of bloodstains, in particular the vertical component is determined more precisely than using conventional methods. In both cases relevant forensic conclusions regarding the course of events were enabled by the ballistic bloodstain pattern analysis.
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We investigated the effect of image size on saccade amplitudes. First, in a meta-analysis, relevant results from previous scene perception studies are summarised, suggesting the possibility of a linear relationship between mean saccade amplitude and image size. Forty-eight observers viewed 96 colour scene images scaled to four different sizes, while their eye movements were recorded. Mean and median saccade amplitudes were found to be directly proportional to image size, while the mode of the distribution lay in the range of very short saccades. However, saccade amplitudes expressed as percentages of image size were not constant over the different image sizes; on smaller stimulus images, the relative saccades were found to be larger, and vice versa. In sum, and as far as mean and median saccade amplitudes are concerned, the size of stimulus images is the dominant factor. Other factors, such as image properties, viewing task, or measurement equipment, are only of subordinate importance. Thus, the role of stimulus size has to be reconsidered, in theoretical as well as methodological terms.
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Many applications, such as telepresence, virtual reality, and interactive walkthroughs, require a three-dimensional(3D)model of real-world environments. Methods, such as lightfields, geometric reconstruction and computer vision use cameras to acquire visual samples of the environment and construct a model. Unfortunately, obtaining models of real-world locations is a challenging task. In particular, important environments are often actively in use, containing moving objects, such as people entering and leaving the scene. The methods previously listed have difficulty in capturing the color and structure of the environment while in the presence of moving and temporary occluders. We describe a class of cameras called lag cameras. The main concept is to generalize a camera to take samples over space and time. Such a camera, can easily and interactively detect moving objects while continuously moving through the environment. Moreover, since both the lag camera and occluder are moving, the scene behind the occluder is captured by the lag camera even from viewpoints where the occluder lies in between the lag camera and the hidden scene. We demonstrate an implementation of a lag camera, complete with analysis and captured environments.
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The analysis and reconstruction of forensically relevant events, such as traffic accidents, criminal assaults and homicides are based on external and internal morphological findings of the injured or deceased person. For this approach high-tech methods are gaining increasing importance in forensic investigations. The non-contact optical 3D digitising system GOM ATOS is applied as a suitable tool for whole body surface and wound documentation and analysis in order to identify injury-causing instruments and to reconstruct the course of event. In addition to the surface documentation, cross-sectional imaging methods deliver medical internal findings of the body. These 3D data are fused into a whole body model of the deceased. Additional to the findings of the bodies, the injury inflicting instruments and incident scene is documented in 3D. The 3D data of the incident scene, generated by 3D laser scanning and photogrammetry, is also included into the reconstruction. Two cases illustrate the methods. In the fist case a man was shot in his bedroom and the main question was, if the offender shot the man intentionally or accidentally, as he declared. In the second case a woman was hit by a car, driving backwards into a garage. It was unclear if the driver drove backwards once or twice, which would indicate that he willingly injured and killed the woman. With this work, we demonstrate how 3D documentation, data merging and animation enable to answer reconstructive questions regarding the dynamic development of patterned injuries, and how this leads to a real data based reconstruction of the course of event.
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In practical forensic casework, backspatter recovered from shooters' hands can be an indicator of self-inflicted gunshot wounds to the head. In such cases, backspatter retrieved from inside the barrel indicates that the weapon found at the death scene was involved in causing the injury to the head. However, systematic research on the aspects conditioning presence, amount and specific patterns of backspatter is lacking so far. Herein, a new concept of backspatter investigation is presented, comprising staining technique, weapon and target medium: the 'triple contrast method' was developed, tested and is introduced for experimental backspatter analysis. First, mixtures of various proportions of acrylic paint for optical detection, barium sulphate for radiocontrast imaging in computed tomography and fresh human blood for PCR-based DNA profiling were generated (triple mixture) and tested for DNA quantification and short tandem repeat (STR) typing success. All tested mixtures yielded sufficient DNA that produced full STR profiles suitable for forensic identification. Then, for backspatter analysis, sealed foil bags containing the triple mixture were attached to plastic bottles filled with 10 % ballistic gelatine and covered by a 2-3-mm layer of silicone. To simulate backspatter, close contact shots were fired at these models. Endoscopy of the barrel inside revealed coloured backspatter containing typable DNA and radiographic imaging showed a contrasted bullet path in the gelatine. Cross sections of the gelatine core exhibited cracks and fissures stained by the acrylic paint facilitating wound ballistic analysis.
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Recently, vision-based advanced driver-assistance systems (ADAS) have received a new increased interest to enhance driving safety. In particular, due to its high performance–cost ratio, mono-camera systems are arising as the main focus of this field of work. In this paper we present a novel on-board road modeling and vehicle detection system, which is a part of the result of the European I-WAY project. The system relies on a robust estimation of the perspective of the scene, which adapts to the dynamics of the vehicle and generates a stabilized rectified image of the road plane. This rectified plane is used by a recursive Bayesian classi- fier, which classifies pixels as belonging to different classes corresponding to the elements of interest of the scenario. This stage works as an intermediate layer that isolates subsequent modules since it absorbs the inherent variability of the scene. The system has been tested on-road, in different scenarios, including varied illumination and adverse weather conditions, and the results have been proved to be remarkable even for such complex scenarios.
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The application of thematic maps obtained through the classification of remote images needs the obtained products with an optimal accuracy. The registered images from the airplanes display a very satisfactory spatial resolution, but the classical methods of thematic classification not always give better results than when the registered data from satellite are used. In order to improve these results of classification, in this work, the LIDAR sensor data from first return (Light Detection And Ranging) registered simultaneously with the spectral sensor data from airborne are jointly used. The final results of the thematic classification of the scene object of study have been obtained, quantified and discussed with and without LIDAR data, after applying different methods: Maximum Likehood Classification, Support Vector Machine with four different functions kernel and Isodata clustering algorithm (ML, SVM-L, SVM-P, SVM-RBF, SVM-S, Isodata). The best results are obtained for SVM with Sigmoide kernel. These allow the correlation with others different physical parameters with great interest like Manning hydraulic coefficient, for their incorporation in a GIS and their application in hydraulic modeling.
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Quality assessment is a key factor for stereoscopic 3D video content as some observers are affected by visual discomfort in the eye when viewing 3D video, especially when combining positive and negative parallax with fast motion. In this paper, we propose techniques to assess objective quality related to motion and depth maps, which facilitate depth perception analysis. Subjective tests were carried out in order to understand the source of the problem. Motion is an important feature affecting 3D experience but also often the cause of visual discomfort. The automatic algorithm developed tries to quantify the impact on viewer experience when common cases of discomfort occur, such as high-motion sequences, scene changes with abrupt parallax changes, or complete absence of stereoscopy, with a goal of preventing the viewer from having a bad stereoscopic experience.
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In this paper, we present a depth-color scene modeling strategy for indoors 3D contents generation. It combines depth and visual information provided by a low-cost active depth camera to improve the accuracy of the acquired depth maps considering the different dynamic nature of the scene elements. Accurate depth and color models of the scene background are iteratively built, and used to detect moving elements in the scene. The acquired depth data is continuously processed with an innovative joint-bilateral filter that efficiently combines depth and visual information thanks to the analysis of an edge-uncertainty map and the detected foreground regions. The main advantages of the proposed approach are: removing depth maps spatial noise and temporal random fluctuations; refining depth data at object boundaries, generating iteratively a robust depth and color background model and an accurate moving object silhouette.
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A set of ten RADARSAT-2 images acquired in fully polarimetric mode over a test site with rice fields in Seville, Spain, has been analyzed to extract the main features of the C-band radar backscatter as a function of rice phenology. After observing the evolutions versus phenology of different polarimetric observables and explaining their behavior in terms of scattering mechanisms present in the scene, a simple retrieval approach has been proposed. This algorithm is based on three polarimetric observables and provides estimates from a set of four relevant intervals of phenological stages. The validation against ground data, carried out at parcel level for a set of six stands and up to nine dates per stand, provides a 96% rate of coincidence. Moreover, an equivalent compact-pol retrieval algorithm has been also proposed and validated, providing the same performance at parcel level. In all cases, the inversion is carried out by exploiting a single satellite acquisition, without any other auxiliary information.
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"COO-2118-0028."