Visual search and VDUS

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

Efficient Algorithms for Large-Scale Image Analysis

This work develops highly efficient algorithms for analyzing large images. Applications include object-based change detection and screening. The algorithms are 10-100 times as fast as existing software, sometimes even outperforming FGPA/GPU hardware, because they are designed to suit the computer architecture. This thesis describes the implementation details and the underlying algorithm engineering methodology, so that both may also be applied to other applications

Text Segmentation in Web Images Using Colour Perception and Topological Features

The research presented in this thesis addresses the problem of Text Segmentation in Web images. Text is routinely created in image form (headers, banners etc.) on Web pages, as an attempt to overcome the stylistic limitations of HTML. This text however, has a potentially high semantic value in terms of indexing and searching for the corresponding Web pages. As current search engine technology does not allow for text extraction and recognition in images, the text in image form is ignored. Moreover, it is desirable to obtain a uniform representation of all visible text of a Web page (for applications such as voice browsing or automated content analysis). This thesis presents two methods for text segmentation in Web images using colour perception and topological features. The nature of Web images and the implicit problems to text segmentation are described, and a study is performed to assess the magnitude of the problem and establish the need for automated text segmentation methods. Two segmentation methods are subsequently presented: the Split-and-Merge segmentation method and the Fuzzy segmentation method. Although approached in a distinctly different way in each method, the safe assumption that a human being should be able to read the text in any given Web Image is the foundation of both methods’ reasoning. This anthropocentric character of the methods along with the use of topological features of connected components, comprise the underlying working principles of the methods. An approach for classifying the connected components resulting from the segmentation methods as either characters or parts of the background is also presented

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 355)

This bibliography lists 147 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during October, 1991. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

Stereological techniques for synthesizing solid textures from images of aggregate materials

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2005.Includes bibliographical references (leaves 121-130).When creating photorealistic digital scenes, textures are commonly used to depict complex variation in surface appearance. For materials that have spatial variation in three dimensions, such as wood or marble, solid textures offer a natural representation. Unlike 2D textures, which can be easily captured with a photograph, it can be difficult to obtain a 3D material volume. This thesis addresses the challenge of extrapolating tileable 3D solid textures from images of aggregate materials, such as concrete, asphalt, terrazzo or granite. The approach introduced here is inspired by and builds on prior work in stereology--the study of 3D properties of a material based on 2D observations. Unlike ad hoc methods for texture synthesis, this approach has rigorous mathematical foundations that allow for reliable, accurate material synthesis with well-defined assumptions. The algorithm is also driven by psychophysical constraints to insure that slices through the synthesized volume have a perceptually similar appearance to the input image. The texture synthesis algorithm uses a variety of techniques to independently solve for the shape, distribution, and color of the embedded particles, as well as the residual noise. To approximate particle shape, I consider four methods-including two algorithms of my own contribution. I compare these methods under a variety of input conditions using automated, perceptually-motivated metrics as well as a carefully controlled psychophysical experiment. In addition to assessing the relative performance of the four algorithms, I also evaluate the reliability of the automated metrics in predicting the results of the user study. To solve for the particle distribution, I apply traditional stereological methods.(cont.) I first illustrate this approach for aggregate materials of spherical particles and then extend the technique to apply to particles of arbitrary shapes. The particle shape and distribution are used in conjunction to create an explicit 3D material volume using simulated annealing. Particle colors are assigned using a stochastic method, and high-frequency noise is replicated with the assistance of existing algorithms. The data representation is suitable for high-fidelity rendering and physical simulation. I demonstrate the effectiveness of the approach with side-by-side comparisons of real materials and their synthetic counterparts derived from the application of these techniques.by Robert Carl Jagnow.Ph.D

Visual Descriptors: A Design Tool for Visual Impact Analysis

This study is concerned with the development of a practical and effective form of computer-aided analysis of the visual impact of building development in rural areas. Its contribution is fourfold. Firstly, a conceptual model has been developed for the process of seeing in the context of visual impact analysis. Secondly, a mathematical model for a consistent series of visual descriptors has been devised. Thirdly, a suitable design tool has been devised to make use of visual descriptors in visual impact analysis. Fourthly, visual descriptors have actually been implemented as computer software. The concept of visual impact analysis is defined and placed within the wider context of landscape research. The problems faced by a designer in the context of visual impact analysis are identified and the concept of a 'design tool' is introduced and defined. A number of existing computer software packages, intended or used for visual impact analysis, are reviewed critically. The concept of 'visual descriptors' as measures to be used by designers is introduced and examined critically. A conceptual model is presented for the process of seeing in the context of visual impact analysis. A range of possible measures for use as visual descriptors is presented and developed further into a series of precise definitions. A method of implementing visual descriptors is presented together with formal algorithms for the derivation of eight visual descriptors. A software package incorporating these descriptors is presented and verification and case studies of its use carried out. Visual descriptors, as implemented, are assessed for their effectiveness as a design tool for visual impact analysis.Strathclyde University Dept. of Architecture and Building Scienc

Perceptually Modulated Level of Detail for Virtual Environments

Institute for Computing Systems ArchitectureThis thesis presents a generic and principled solution for optimising the visual complexity of any arbitrary computer-generated virtual environment (VE). This is performed with the ultimate goal of reducing the inherent latencies of current virtual reality (VR) technology. Effectively, we wish to remove extraneous detail from an environment which the user cannot perceive, and thus modulate the graphical complexity of a VE with little or no perceptual artifacts. The work proceeds by investigating contemporary models and theories of visual perception and then applying these to the field of real-time computer graphics. Subsequently, a technique is devised to assess the perceptual content of a computer-generated image in terms of spatial frequency (c/deg), and a model of contrast sensitivity is formulated to describe a user's ability to perceive detail under various conditions in terms of this metric. This allows us to base the level of detail (LOD) of each object in a VE on a measure of the degree of spatial detail which the user can perceive at any instant (taking into consideration the size of an object, its angular velocity, and the degree to which it exists in the peripheral field). Additionally, a generic polygon simplification framework is presented to complement the use of perceptually modulated LOD. The efficient implementation of this perceptual model is discussed and a prototype system is evaluated through a suite of experiments. These include a number of low-level psychophysical studies (to evaluate the accuracy of the model), a task performance study (to evaluate the effects of the model on the user), and an analysis of system performance gain (to evaluate the effects of the model on the system). The results show that for the test application chosen, the frame rate of the simulation was manifestly improved (by four to five-fold) with no perceivable drop in image fidelity. As a result, users were able to perform the given wayfinding task more proficiently and rapidly. Finally, conclusions are drawn on the application and utility of perceptually-based optimisations; both in reference to this work, and in the wider context

TOWARDS A COMPUTATIONAL MODEL OF RETINAL STRUCTURE AND BEHAVIOR

Human vision is our most important sensory system, allowing us to perceive our surroundings. It is an extremely complex process that starts with light entering the eye and ends inside of the brain, with most of its mechanisms still to be explained. When we observe a scene, the optics of the eye focus an image on the retina, where light signals are processed and sent all the way to the visual cortex of the brain, enabling our visual sensation. The progress of retinal research, especially on the topography of photoreceptors, is often tied to the progress of retinal imaging systems. The latest adaptive optics techniques have been essential for the study of the photoreceptors and their spatial characteristics, leading to discoveries that challenge the existing theories on color sensation. The organization of the retina is associated with various perceptive phenomena, some of them are straightforward and strictly related to visual performance like visual acuity or contrast sensitivity, but some of them are more difficult to analyze and test and can be related to the submosaics of the three classes of cone photoreceptors, like how the huge interpersonal differences between the ratio of different cone classes result in negligible differences in color sensation, suggesting the presence of compensation mechanisms in some stage of the visual system. In this dissertation will be discussed and addressed issues regarding the spatial organization of the photoreceptors in the human retina. A computational model has been developed, organized into a modular pipeline of extensible methods each simulating a different stage of visual processing. It does so by creating a model of spatial distribution of cones inside of a retina, then applying descriptive statistics for each photoreceptor to contribute to the creation of a graphical representation, based on a behavioral model that determines the absorption of photoreceptors. These apparent color stimuli are reconstructed in a representation of the observed scene. The model allows the testing of different parameters regulating the photoreceptor's topography, in order to formulate hypothesis on the perceptual differences arising from variations in spatial organization

Optimal prefilters for display enhancement

Creating images from a set of discrete samples is arguably the most common operation in computer graphics and image processing, lying, for example, at the heart of rendering and image downscaling techniques. Traditional tools for this task are based on classic sampling theory and are modeled under mathematical conditions which are, in most cases, unrealistic; for example, sinc reconstruction – required by Shannon theorem in order to recover a signal exactly – is impossible to achieve in practice because LCD displays perform a box-like interpolation of the samples. Moreover, when an image is made for a human to look at, it will necessarily undergo some modifications due to the human optical system and all the neural processes involved in vision. Finally, image processing practitioners noticed that sinc prefiltering – also required by Shannon theorem – often leads to visually unpleasant images. From these facts, we can deduce that we cannot guarantee, via classic sampling theory, that the signal we see in a display is the best representation of the original image we had in first place. In this work, we propose a novel family of image prefilters based on modern sampling theory, and on a simple model of how the human visual system perceives an image on a display. The use of modern sampling theory guarantees us that the perceived image, based on this model, is indeed the best representation possible, and at virtually no computational overhead. We analyze the spectral properties of these prefilters, showing that they offer the possibility of trading-off aliasing and ringing, while guaranteeing that images look sharper then those generated with both classic and state-of-the-art filters. Finally, we compare it against other solutions in a selection of applications which include Monte Carlo rendering and image downscaling, also giving directions on how to apply it in different contexts.Exibir imagens a partir de um conjunto discreto de amostras é certamente uma das operações mais comuns em computação gráfica e processamento de imagens. Ferramentas tradicionais para essa tarefa são baseadas no teorema de Shannon e são modeladas em condições matemáticas que são, na maior parte dos casos, irrealistas; por exemplo, reconstrução com sinc – necessária pelo teorema de Shannon para recuperar um sinal exatamente – é impossível na prática, já que displays LCD realizam uma reconstrução mais próxima de uma interpolação com kernel box. Além disso, profissionais em processamento de imagem perceberam que prefiltragem com sinc – também requerida pelo teorema de Shannon – em geral leva a imagens visualmente desagradáveis devido ao fenômeno de ringing: oscilações próximas a regiões de descontinuidade nas imagens. Desses fatos, deduzimos que não é possível garantir, via ferramentas tradicionais de amostragem e reconstrução, que a imagem que observamos em um display digital é a melhor representação para a imagem original. Neste trabalho, propomos uma família de prefiltros baseada em teoria de amostragem generalizada e em um modelo de como o sistema ótico do olho humano modifica uma imagem. Proposta por Unser and Aldroubi (1994), a teoria de amostragem generalizada é mais geral que o teorema proposto por Shannon, e mostra como é possível pré-filtrar e reconstruir sinais usando kernels diferentes do sinc. Modelamos o sistema ótico do olho como uma câmera com abertura finita e uma lente delgada, o que apesar de ser simples é suficiente para os nossos propósitos. Além de garantir aproximação ótima quando reconstruindo as amostras por um display e filtrando a imagem com o modelo do sistema ótico humano, a teoria de amostragem generalizada garante que essas operações são extremamente eficientes, todas lineares no número de pixels de entrada. Também, analisamos as propriedades espectrais desses filtros e de técnicas semelhantes na literatura, mostrando que é possível obter um bom tradeoff entre aliasing e ringing (principais artefatos quando lidamos com amostragem e reconstrução de imagens), enquanto garantimos que as imagens finais são mais nítidas que aquelas geradas por técnicas existentes na literatura. Finalmente, mostramos algumas aplicações da nossa técnica em melhoria de imagens, adaptação à distâncias de visualização diferentes, redução de imagens e renderização de imagens sintéticas por método de Monte Carlo

Material Visualisation for Virtual Reality: The Perceptual Investigations

Material representation plays a significant role in design visualisation and evaluation. On one hand, the simulated material properties determine the appearance of product prototypes in digitally rendered scenes. On the other hand, those properties are perceived by the viewers in order to make important design decisions. As an approach to simulate a more realistic environment, Virtual Reality (VR) provides users a vivid impression of depth and embodies them into an immersive environment. However, the scientific understanding of material perception and its applications in VR is still fairly limited. This leads to this thesis’s research question on whether the material perception in VR is different from that in traditional 2D displays, as well as the potential of using VR as a design tool to facilitate material evaluation.       This thesis is initiated from studying the perceptual difference of rendered materials between VR and traditional 2D viewing modes. Firstly, through a pilot study, it is confirmed that users have different perceptual experiences of the same material in the two viewing modes. Following that initial finding, the research investigates in more details the perceptual difference with psychophysics methods, which help in quantifying the users’ perceptual responses. Using the perceptual scale as a measuring means, the research analyses the users’ judgment and recognition of the material properties under VR and traditional 2D display environments. In addition, the research also elicits the perceptual evaluation criteria to analyse the emotional aspects of materials. The six perceptual criteria are in semantic forms, including rigidity, formality, fineness, softness, modernity, and irregularity.       The results showed that VR could support users in making a more refined judgment of material properties. That is to say, the users perceive better the minute changes of material properties under immersive viewing conditions. In terms of emotional aspects, VR is advantageous in signifying the effects induced by visual textures, while the 2D viewing mode is more effective for expressing the characteristics of plain surfaces. This thesis has contributed to the deeper understanding of users’ perception of material appearances in Virtual Reality, which is critical in achieving an effective design visualisation using such a display medium