35 research outputs found

    Visual search and VDUS

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    This wide-ranging study explored various parameters of visual search in relation to computer screen displays. Its ultimate goal was to help identify factors which could result in improvements in commercially available displays within the 'real world’. Those improvements are generally reflected in suggestions for enhancing efficiency of locatabolity of information through an acknowledgement of the visual and cognitive factors involved. The thesis commenced by introducing an ergonomics approach to the presentation of information on VDUs. Memory load and attention were discussed. In the second chapter, literature on general and theoretical aspects of visual search (with particular regard for VDUs) was reviewed. As an experimental starting point, three studies were conducted involving locating a target within arrays of varying configurations. A model concerning visual lobes was proposed. Two text-editing studies were then detailed showing superior user performances where conspicuity and the potential for peripheral vision are enhanced. Relevant eye movement data was combined with a keystroke analysis derived from an automated protocol analyser. Results of a further search task showed icons to be more quickly located within an array than textual material. Precise scan paths were then recorded and analyses suggested greater systematicity of search strategies for complex items. This led on to a relatively 'pure' search study involving materials of varying spatial frequencies. Results were discussed in terms of verbal material generally being of higher spatial frequencies and how the ease of resolution and greater cues available in peripheral vision can result in items being accessed more directly. In the final (relatively applied) study, differences in eye movement indices were found across various fonts used. One main conclusion was that eye movement monitoring was a valuable technique within the visual search/VDU research area in illuminating precise details of performance which otherwise, at best, could only be inferred

    Text and Genre in Reconstruction

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    In this broad-reaching, multi-disciplinary collection, leading scholars investigate how the digital medium has altered the way we read and write text. In doing so, it challenges the very notion of scholarship as it has traditionally been imagined. Incorporating scientific, socio-historical, materialist and theoretical approaches, this rich body of work explores topics ranging from how computers have affected our relationship to language, whether the book has become an obsolete object, the nature of online journalism, and the psychology of authorship. The essays offer a significant contribution to the growing debate on how digitization is shaping our collective identity, for better or worse. Text and Genre in Reconstruction will appeal to scholars in both the humanities and sciences and provides essential reading for anyone interested in the changing relationship between reader and text in the digital age

    TOWARDS A MODEL FOR ARTIFICIAL AESTHETICS - Contributions to the Study of Creative Practices in Procedural and Computational Systems

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    Este trabalho propõe o desenvolvimento de um modelo analítico e da terminologia a ele associada para o estudo de artefactos estéticos computacionais. Reconhecendo a presença e uso crescentes dos media computacionais, começamos por estudar como através da remediação eles transformam quantitativamente os media precedentes, e como as suas propriedades procedimentais e computacionais os afectam qualitativamente. Para perceber o potencial criativo e a especificidade dos media computacionais, desenvolvemos um modelo para a sua prática, crítica e análise. Como ponto de partida recorremos à tipologia desenvolvida por Espen Aarseth para o estudo de cibertextos, avaliando a sua adequação à análise de peças ergódicas visuais e audiovisuais, adaptando-a e expandindo-a com novas variáveis e respectivos valores. O modelo é testado através da análise de um conjunto de peças que representam diversas abordagens à criação procedimental e diversas áreas de actividade criativa contemporânea. É posteriormente desenvolvida uma análise de controlo para avaliar a usabilidade e utilidade do modelo, a sua capacidade para a elaboração de classificações objectivas e o rigor da análise. Demonstramos a adequação parcial do modelo de Aarseth para o estudo de artefactos não textuais e expandimo-lo para melhor descrever as peças estudadas. Concluímos que o modelo apresentado produz boas descrições das peças, agrupando-as logicamente, reflectindo afinidades estilísticas e procedimentais entre sistemas que, se estudados com base nas suas propriedades sensoriais ou nas suas estruturas de superfície provavelmente não revelariam muitas semelhanças. As afinidades reveladas pelo modelo são estruturais e procedimentais, e atestam a importância das características computacionais para a apreciação estética das obras. Verificamos a nossa conjectura inicial sobre a importância da procedimentalidade não só nas fases de desenvolvimento e implementação das obras mas também como base conceptual e estética na criação e apreciação artísticas, como um prazer estético

    Text and Genre in Reconstruction

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    In this broad-reaching, multi-disciplinary collection, leading scholars investigate how the digital medium has altered the way we read and write text. In doing so, it challenges the very notion of scholarship as it has traditionally been imagined. Incorporating scientific, socio-historical, materialist and theoretical approaches, this rich body of work explores topics ranging from how computers have affected our relationship to language, whether the book has become an obsolete object, the nature of online journalism, and the psychology of authorship. The essays offer a significant contribution to the growing debate on how digitization is shaping our collective identity, for better or worse. Text and Genre in Reconstruction will appeal to scholars in both the humanities and sciences and provides essential reading for anyone interested in the changing relationship between reader and text in the digital age

    Expressive movement generation with machine learning

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    Movement is an essential aspect of our lives. Not only do we move to interact with our physical environment, but we also express ourselves and communicate with others through our movements. In an increasingly computerized world where various technologies and devices surround us, our movements are essential parts of our interaction with and consumption of computational devices and artifacts. In this context, incorporating an understanding of our movements within the design of the technologies surrounding us can significantly improve our daily experiences. This need has given rise to the field of movement computing – developing computational models of movement that can perceive, manipulate, and generate movements. In this thesis, we contribute to the field of movement computing by building machine-learning-based solutions for automatic movement generation. In particular, we focus on using machine learning techniques and motion capture data to create controllable, generative movement models. We also contribute to the field by creating datasets, tools, and libraries that we have developed during our research. We start our research by reviewing the works on building automatic movement generation systems using machine learning techniques and motion capture data. Our review covers background topics such as high-level movement characterization, training data, features representation, machine learning models, and evaluation methods. Building on our literature review, we present WalkNet, an interactive agent walking movement controller based on neural networks. The expressivity of virtual, animated agents plays an essential role in their believability. Therefore, WalkNet integrates controlling the expressive qualities of movement with the goal-oriented behaviour of an animated virtual agent. It allows us to control the generation based on the valence and arousal levels of affect, the movement’s walking direction, and the mover’s movement signature in real-time. Following WalkNet, we look at controlling movement generation using more complex stimuli such as music represented by audio signals (i.e., non-symbolic music). Music-driven dance generation involves a highly non-linear mapping between temporally dense stimuli (i.e., the audio signal) and movements, which renders a more challenging modelling movement problem. To this end, we present GrooveNet, a real-time machine learning model for music-driven dance generation

    A framework for ancient and machine-printed manuscripts categorization

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    Document image understanding (DIU) has attracted a lot of attention and became an of active fields of research. Although, the ultimate goal of DIU is extracting textual information of a document image, many steps are involved in a such a process such as categorization, segmentation and layout analysis. All of these steps are needed in order to obtain an accurate result from character recognition or word recognition of a document image. One of the important steps in DIU is document image categorization (DIC) that is needed in many situations such as document image written or printed in more than one script, font or language. This step provides useful information for recognition system and helps in reducing its error by allowing to incorporate a category-specific Optical Character Recognition (OCR) system or word recognition (WR) system. This research focuses on the problem of DIC in different categories of scripts, styles and languages and establishes a framework for flexible representation and feature extraction that can be adapted to many DIC problem. The current methods for DIC have many limitations and drawbacks that restrict the practical usage of these methods. We proposed an efficient framework for categorization of document image based on patch representation and Non-negative Matrix Factorization (NMF). This framework is flexible and can be adapted to different categorization problem. Many methods exist for script identification of document image but few of them addressed the problem in handwritten manuscripts and they have many limitations and drawbacks. Therefore, our first goal is to introduce a novel method for script identification of ancient manuscripts. The proposed method is based on patch representation in which the patches are extracted using skeleton map of a document images. This representation overcomes the limitation of the current methods about the fixed level of layout. The proposed feature extraction scheme based on Projective Non-negative Matrix Factorization (PNMF) is robust against noise and handwriting variation and can be used for different scripts. The proposed method has higher performance compared to state of the art methods and can be applied to different levels of layout. The current methods for font (style) identification are mostly proposed to be applied on machine-printed document image and many of them can only be used for a specific level of layout. Therefore, we proposed new method for font and style identification of printed and handwritten manuscripts based on patch representation and Non-negative Matrix Tri-Factorization (NMTF). The images are represented by overlapping patches obtained from the foreground pixels. The position of these patches are set based on skeleton map to reduce the number of patches. Non-Negative Matrix Tri-Factorization is used to learn bases from each fonts (style) and then these bases are used to classify a new image based on minimum representation error. The proposed method can easily be extended to new fonts as the bases for each font are learned separately from the other fonts. This method is tested on two datasets of machine-printed and ancient manuscript and the results confirmed its performance compared to the state of the art methods. Finally, we proposed a novel method for language identification of printed and handwritten manuscripts based on patch representation and Non-negative Matrix Tri-Factorization (NMTF). The current methods for language identification are based on textual data obtained by OCR engine or images data through coding and comparing with textual data. The OCR based method needs lots of processing and the current image based method are not applicable to cursive scripts such as Arabic. In this work we introduced a new method for language identification of machine-printed and handwritten manuscripts based on patch representation and NMTF. The patch representation provides the component of the Arabic script (letters) that can not be extracted simply by segmentation methods. Then NMTF is used for dictionary learning and generating codebooks that will be used to represent document image with a histogram. The proposed method is tested on two datasets of machine-printed and handwritten manuscripts and compared to n-gram features (text-based), texture features and codebook features (imagebased) to validate the performance. The above proposed methods are robust against variation in handwritings, changes in the font (handwriting style) and presence of degradation and are flexible that can be used to various levels of layout (from a textline to paragraph). The methods in this research have been tested on datasets of handwritten and machine-printed manuscripts and compared to state-of-the-art methods. All of the evaluations show the efficiency, robustness and flexibility of the proposed methods for categorization of document image. As mentioned before the proposed strategies provide a framework for efficient and flexible representation and feature extraction for document image categorization. This frame work can be applied to different levels of layout, the information from different levels of layout can be merged and mixed and this framework can be extended to more complex situations and different tasks

    Reading Today

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    New technologies are changing our reading habits. Laptops, e-readers, tablets and other handheld devices supply new platforms for reading, and we must learn to manage them by scrolling, clicking or tapping. Reading Today places reading in current literary and cultural contexts in order to analyse how these contexts challenge our conceptions of who reads, what reading is, how we read, where we read, and for what purposes – and then responds to the questions this analysis raises. Is our reading experience becoming a ‘flat’ one? And does reading in a media environment favour quick reading? Alongside these questions, the contributors unpack emerging strategies of reading.They consider, for example, how paying attention to readers’ emotional reactions as an indispensable component of reading affects our conception of the reading process. Other chapters consider how reading can be explored through such topics as experimental literature, the contemporary encyclopedic novel and the healing power of books

    Digital Media and Textuality: From Creation to Archiving

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    Due to computers' ability to combine different semiotic modes, texts are no longer exclusively comprised of static images and mute words. How have digital media changed the way we write and read? What methods of textual and data analysis have emerged? How do we rescue digital artifacts from obsolescence? And how can digital media be used or taught inside classrooms? These and other questions are addressed in this volume that assembles contributions by artists, writers, scholars and editors. They offer a multiperspectival view on the way digital media have changed our notion of textuality

    Digital Media and Textuality

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    Due to computers' ability to combine different semiotic modes, texts are no longer exclusively comprised of static images and mute words. How have digital media changed the way we write and read? What methods of textual and data analysis have emerged? How do we rescue digital artifacts from obsolescence? And how can digital media be used or taught inside classrooms? These and other questions are addressed in this volume that assembles contributions by artists, writers, scholars and editors such as Dene Grigar, Sandy Baldwin, Carlos Reis, and Frieder Nake. They offer a multiperspectival view on the way digital media have changed our notion of textuality
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