Disparity map generation based on trapezoidal camera architecture for multiview video

Visual content acquisition is a strategic functional block of any visual system. Despite its wide possibilities, the arrangement of cameras for the acquisition of good quality visual content for use in multi-view video remains a huge challenge. This paper presents the mathematical description of trapezoidal camera architecture and relationships which facilitate the determination of camera position for visual content acquisition in multi-view video, and depth map generation. The strong point of Trapezoidal Camera Architecture is that it allows for adaptive camera topology by which points within the scene, especially the occluded ones can be optically and geometrically viewed from several different viewpoints either on the edge of the trapezoid or inside it. The concept of maximum independent set, trapezoid characteristics, and the fact that the positions of cameras (with the exception of few) differ in their vertical coordinate description could very well be used to address the issue of occlusion which continues to be a major problem in computer vision with regards to the generation of depth map

Neuron-level dynamics of oscillatory network structure and markerless tracking of kinematics during grasping

Oscillatory synchrony is proposed to play an important role in flexible sensory-motor transformations. Thereby, it is assumed that changes in the oscillatory network structure at the level of single neurons lead to flexible information processing. Yet, how the oscillatory network structure at the neuron-level changes with different behavior remains elusive. To address this gap, we examined changes in the fronto-parietal oscillatory network structure at the neuron-level, while monkeys performed a flexible sensory-motor grasping task. We found that neurons formed separate subnetworks in the low frequency and beta bands. The beta subnetwork was active during steady states and the low frequency network during active states of the task, suggesting that both frequencies are mutually exclusive at the neuron-level. Furthermore, both frequency subnetworks reconfigured at the neuron-level for different grip and context conditions, which was mostly lost at any scale larger than neurons in the network. Our results, therefore, suggest that the oscillatory network structure at the neuron-level meets the necessary requirements for the coordination of flexible sensory-motor transformations. Supplementarily, tracking hand kinematics is a crucial experimental requirement to analyze neuronal control of grasp movements. To this end, a 3D markerless, gloveless hand tracking system was developed using computer vision and deep learning techniques. 2021-11-3

Camera positioning for 3D panoramic image rendering

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University London.Virtual camera realisation and the proposition of trapezoidal camera architecture are the two broad contributions of this thesis. Firstly, multiple camera and their arrangement constitute a critical component which affect the integrity of visual content acquisition for multi-view video. Currently, linear, convergence, and divergence arrays are the prominent camera topologies adopted. However, the large number of cameras required and their synchronisation are two of prominent challenges usually encountered. The use of virtual cameras can significantly reduce the number of physical cameras used with respect to any of the known camera structures, hence adequately reducing some of the other implementation issues. This thesis explores to use image-based rendering with and without geometry in the implementations leading to the realisation of virtual cameras. The virtual camera implementation was carried out from the perspective of depth map (geometry) and use of multiple image samples (no geometry). Prior to the virtual camera realisation, the generation of depth map was investigated using region match measures widely known for solving image point correspondence problem. The constructed depth maps have been compare with the ones generated using the dynamic programming approach. In both the geometry and no geometry approaches, the virtual cameras lead to the rendering of views from a textured depth map, construction of 3D panoramic image of a scene by stitching multiple image samples and performing superposition on them, and computation of virtual scene from a stereo pair of panoramic images. The quality of these rendered images were assessed through the use of either objective or subjective analysis in Imatest software. Further more, metric reconstruction of a scene was performed by re-projection of the pixel points from multiple image samples with a single centre of projection. This was done using sparse bundle adjustment algorithm. The statistical summary obtained after the application of this algorithm provides a gauge for the efficiency of the optimisation step. The optimised data was then visualised in Meshlab software environment, hence providing the reconstructed scene. Secondly, with any of the well-established camera arrangements, all cameras are usually constrained to the same horizontal plane. Therefore, occlusion becomes an extremely challenging problem, and a robust camera set-up is required in order to resolve strongly the hidden part of any scene objects. To adequately meet the visibility condition for scene objects and given that occlusion of the same scene objects can occur, a multi-plane camera structure is highly desirable. Therefore, this thesis also explore trapezoidal camera structure for image acquisition. The approach here is to assess the feasibility and potential of several physical cameras of the same model being sparsely arranged on the edge of an efficient trapezoid graph. This is implemented both Matlab and Maya. The quality of the depth maps rendered in Matlab are better in Quality

Producing Decisions and Explanations: A Joint Approach Towards Explainable CNNs

Deep Learning models, in particular Convolutional Neural Networks, have become the state-of-the-art in different domains, such as image classification, object detection and other computer vision tasks. However, despite their overwhelming predictive performance, they are still, for the most part, considered black-boxes, making it difficult to understand the reasoning behind their outputted decisions. As such, and with the growing interest in deploying such models into real world scenarios, the need for explainable systems has arisen. Therefore, this dissertation tries to mitigate this growing need, by proposing a novel CNN architecture, composed of an explainer and a classifier. The network, trained end-to-end, constitutes an in-model explainability method, that not only outputs decisions as well as visual explanations of what the network is focusing on to produce such decisions

A right hemisphere advantage for processing blurred faces

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Comparison of the vocabularies of the Gregg shorthand dictionary and Horn-Peterson's basic vocabulary of business letters

This study is a comparative analysis of the vocabularies of Horn and Peterson's The Basic Vocabulary of Business Letters1 and the Gregg Shorthand Dictionary.2 Both books purport to present a list of words most frequently encountered by stenographers and students of shorthand. The, Basic Vocabulary of Business Letters, published "in answer to repeated requests for data on the words appearing most frequently in business letters,"3 is a frequency list specific to business writing. Although the book carries the copyright date of 1943, the vocabulary was compiled much earlier. The listings constitute a part of the data used in the preparation of the 10,000 words making up the ranked frequency list compiled by Ernest Horn and staff and published in 1926 under the title of A Basic Writing Vocabulary: 10,000 Words Lost Commonly Used in Writing. The introduction to that publication gives credit to Miss Cora Crowder for the contribution of her Master's study at the University of Minnesota concerning words found in business writing. With additional data from supplementary sources, the complete listing represents twenty-six classes of business, as follows 1. Miscellaneous 2. Florists 3. Automobile manufacturers and sales companie

Exceptional scale: metafiction and the maximalist tradition in contemporary American literary history

This dissertation reexamines the narrative practice of self-reflexivity through the lens of aesthetic size to advance a new approach to reading long-form novels of the late twentieth and early twenty-first centuries. Whereas previous scholarship on the maximalist tradition relies on the totalizing rhetorics of endlessness, exhaustion, encyclopedism, and excess, I interpret the form’s reflexive awareness of its own enlarged scale as a uniquely narrative “knowledge work” that mediates the reader’s experience of information-rich texts. Thus, my narrative and network theory-informed approach effectively challenges the analytical modes of prominent genre theories such as the Mega-Novel, encyclopedic narrative, the systems novel, and modern epic to propose a critical reading method that recovers the extra-literary discourses through which scalarity is framed. Following this logic, each chapter historicizes prior theories of literary scale in postwar U.S. fiction toward redefining cross-national differences that vary across the boundaries of class, race, ethnicity, religion, gender, and sexuality. Chapter two addresses the scholarly discourse of encyclopedism surrounding the Mega-Novels of Thomas Pynchon and Joseph McElroy. Posing an ethical challenge to popular critiques of metafictional aesthetics, both authors, I argue, contest one of the critical orthodoxies of realist form—the “exceptionality thesis”—which rests on an assumed separation between an audience’s experience of fictional minds in a literary work and its understanding of actual minds in everyday life. In constructing a suitably massive networked platform on which to stage identity as a pluralistic work-in-progress, Gravity’s Rainbow and Women and Men, I contend, narrativize those operations of mind typically occluded from narrative discourse, and so make literal their authors’ meta-ethical visions of a “multiplying real” as much a part of our world as the novel’s own. Chapter three focuses on the mise en abyme as a discursive practice in the labyrinthine narratives of Samuel R. Delany and Mark Z. Danielewski. My analysis posits The Mad Man and House of Leaves as immersive case studies on the academic reading experience by interrogating the satirical strategy of “mock scholarship,” in which a textual object at plot’s center is gradually displaced by the intra-textual reception history that surrounds it. Subtly complicating an increasingly imperceptible line between fact and its fictional counterpart, Delany and Danielewski, I assert, propose new forms of knowledge production through a multiplicity of potential “research spaces” that micromanage the interpretive process while exceeding the structural contours that frame it. Chapter four considers the problem of literary canon formation in the polemical epics of Gayl Jones and Joshua Cohen. Across vast surveys of the stereotypes that mark their marginalization, Jones and Cohen transgress the metaphorical borders constructed between individual voice, collective identity, and the literary institutions that reify “ethnoracial diversity” as a belated form of cultural capital. Explicitly foregrounding the ideological gaps, errors, and omissions against which canonical classification is typically defined, Mosquito and Witz, I suggest, promote not so much a representative widening of the canon’s historically restrictive archive as a complete dissolution of the exclusionary practices it honors and preserves

Centers of Consciousness: Protagonism and the Nineteenth-Century British Novel

Since Aristotle, we have categorized characters in terms of relative quantity and proportion. From Henry James's "center of consciousness," to E. M. Forster's theory of "round" and "flat," to Deidre Lynch's "pragmatics of character," to Alex Woloch's influential "one versus many," scaled distinctions between "major" and "minor" characters have remained unchallenged since the Poetics. Yet such classifications don't capture the ways characters claim amounts of interest and consequence that are disproportionate to their textual presence. My book counters these approaches to character by calling attention to how novels concisely render the rich interior fullness of even very minor figures. While literary critics associate representations of consciousness with major characters, I demonstrate that, through the application of narrative techniques such as first-person narration and focalization, the limited amounts of text allotted to minor characters can yield brief flashes of depth. These depictions of consciousness may lack the "exhaustive presentation" that Ian Watt claims is inherent to the novel, but they are nonetheless brimming with the personality and specificity critics typically associate with central characters. Indeed, many canonical novels, especially those of literary realism's highpoint in nineteenth-century Britain, resist the character hierarchy implied by distinctions such as major and minor. In addition to manifest examples such as Wilkie Collins's "experiment" with many narrators in The Woman in White (1859), we can count instances in which the centrality of a major character is disrupted or challenged. From Mary Shelley's Frankenstein (1818), where the title character's initial prominence is undermined by his creature's arresting autobiography, to George Eliot's Daniel Deronda (1876), in which readerly affections are split between a Jewish hero, an egoistic heroine, and a narrator's attempt to relate "everything" to "everything else," novels that are far from generic outliers fit uneasily into scaled models of characterization, even when their titles and critics imply otherwise. By recuperating the significance of representations of minor characters' consciousnesses, I argue that such novels disrupt the impulse for sustained identification with a single exceptional perspective, directing attention towards characters who might otherwise appear nondescript, inscrutable, threatening, or even inhuman. My rethinking of minor characters' interior fullness allows me to reframe our understanding of the social purpose that Victorian authors such as Dickens and Eliot claim for the novel. As Eliot suggests in "The Natural History of German Life" (1856), literature should "amplif[y] experience and exten[d] our contact with our fellow-men beyond the bounds of our personal lot," resisting stock figures and stereotypes to produce a form of social sympathy that is deliberate, sustained, and self-reflective. This view of the novel's morally instructive capacity is refracted in recent arguments by scholars such as Martha Nussbaum, who claims that readers' involvement with the novel's prolonged form and involved descriptions cultivates their ethical imagination. Yet both Eliot and latter-day critics suspect that the readerly experience of identifying with characters impedes the novel's social utility: the narrator in Middlemarch (1871-2) must ask "But why always Dorothea" of its likeable heroine, while Wayne Booth describes identification as an "immature" approach to literature that occludes "aesthetic experience." Character, however, is not always so all-consuming. I argue that both the brevity and the sheer numerousness of depictions of minor characters' consciousness make them the locus of novels' engagement with socially-oriented sympathy. By countering a protagonist's too-engrossing psychology with many full conscious centers, minor characters both mark and extend beyond novels' textual limits. In their ability to encompass and briefly reorient themselves around these many rich individual points, nineteenth-century novels themselves come to embody an ideally sympathetic perspective: capacious, inclusive, and free of excessive partiality