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Now showing 1 - 10 of 23
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    Immersive WebXR Data Visualisation Tool
    (The Eurographics Association, 2023) Ogbonda, Ebube Glory; Vangorp, Peter; Hunter, David
    This paper presents a study of a WebXR data visualisation tool designed for the immersive exploration of complex datasets in a 3D environment. The application developed using AFrame, D3.js, and JavaScript enables an interactive, device-agnostic platform compatible with various devices and systems. A user study is proposed to assess the tool's usability, user experience, and mental workload using the NASA Task Load Index (NASA TLX). The evaluation is planned to employ questionnaires, task completion times, and open-ended questions to gather feedback and insights. The anticipated results aim to provide insights into the effectiveness of the application in supporting users in understanding and extracting insights from complex data while delivering an engaging and intuitive experience. Future work will refine and expand the tool's capabilities by exploring interaction guidance, visualisation layout optimisation, and long-term user experience assessment. This research contributes to the growing field of immersive data visualisation and informs future tool design.
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    Interweaving Data and Stories: A Case Study on Unveiling the Human Dimension of U.S. Refugee Movements through Narrative Visualisation
    (The Eurographics Association, 2023) Ogbonda, Ebube Glory; Roberts, Jonathan C.; Butcher, Peter W. S.; Vangorp, Peter; Hunter, David
    In response to the escalating global refugee crisis, we present a case-study of developing an advanced tool for interpreting high-dimensional refugee data. Developed using Mapbox and D3.js, our interactive visualisation harmonises geographical and temporal dimensions of U.S. refugee data from the State Department's Refugee Processing Center. Our modular approach and robust data preprocessing enable seamless interactions among diverse visual components. The result is a narrative-driven visualisation that reveals broad immigration trends and individual refugee movements, fostering a nuanced and empathetic understanding of refugee dynamics. This work highlights the power of narrative visualisations in shaping policy decisions and promoting global discourse on the refugee crisis, marking a significant leap in data visualisation for refugee and immigration challenges.
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    Inpainting Normal Maps for Lightstage data
    (The Eurographics Association, 2023) Zuo, Hancheng; Tiddeman, Bernard; Vangorp, Peter; Hunter, David
    This paper presents a new method for inpainting of normal maps using a generative adversarial network (GAN) model. Normal maps can be acquired from a lightstage, and when used for performance capture, there is a risk of areas of the face being obscured by the movement (e.g. by arms, hair or props). Inpainting aims to fill missing areas of an image with plausible data. This work builds on previous work for general image inpainting, using a bow tie-like generator network and a discriminator network, and alternating training of the generator and discriminator. The generator tries to sythesise images that match the ground truth, and that can also fool the discriminator that is classifying real vs processed images. The discriminator is occasionally retrained to improve its performance at identifying the processed images. In addition, our method takes into account the nature of the normal map data, and so requires modification to the loss function. We replace a mean squared error loss with a cosine loss when training the generator. Due to the small amount of available training data available, even when using synthetic datasets, we require significant augmentation, which also needs to take account of the particular nature of the input data. Image flipping and in-plane rotations need to properly flip and rotate the normal vectors. During training, we monitored key performance metrics including average loss, Structural Similarity Index Measure (SSIM), and Peak Signal-to-Noise Ratio (PSNR) of the generator, alongside average loss and accuracy of the discriminator. Our analysis reveals that the proposed model generates high-quality, realistic inpainted normal maps, demonstrating the potential for application to performance capture. The results of this investigation provide a baseline on which future researchers could build with more advanced networks and comparison with inpainting of the source images used to generate the normal maps.
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    Towards Ceramics Inspired Physiotherapy for Recovering Stroke Patients
    (The Eurographics Association, 2023) Hajzer, Sándor P.; Jones, Andra; Jones, David E.; Miles, Helen C.; Ellis, Victoria; Povina, Federico V.; Sganga, Magalí; Swain, Martin T.; Bennett-Gillison, Sophie; Vangorp, Peter; Hunter, David
    People prescribed physiotherapy exercises can struggle to engage with exercises due to a lack of mental stimulation in the repetitive tasks. The introduction of VR to motion-based physiotherapy can be beneficial, however, currently available physiotherapy applications are focused on gaming and the gamification of physiotherapy, something that will not appeal to all patients. This project presents work in-progress towards a VR ceramics painting inspired physiotherapy application, where patients are guided to perform a series of simple motion exercises under the supervision of physiotherapists. Literature shows that art-based therapy can improve patient outcome, and ceramics involves a range of 3D movements that can be aligned with physiotherapy exercises. The work presented is intended to inform future research and development efforts.
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    Using The Barnes-Hut Approximation for Fast N-Body Simulations in Computer Graphics
    (The Eurographics Association, 2023) Dravecky, Peter; Stephenson, Ian; Vangorp, Peter; Hunter, David
    Particle systems in CG often encounter performance issues when all the particles rely on mutual influence, producing an O(N2) performance. The Barnes-Hut approximation is used in the field of astrophysics to provide sufficiently accurate results in O(Nlog(N)) time. Here we explore a hardware accelerated implementation of this algorithm, implemented within SideFX Houdini - the commercial tool typically used for particle work in film. We are able to demonstrate a workflow with integrates into the existing artist friendly environment, with performance improved by orders of magnitudes for typically large simulations, and negligible visual change in results.
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    Classifying User Interface Accessibility for Colourblind Users
    (The Eurographics Association, 2023) Jamil, Amaan; Denes, Gyorgy; Vangorp, Peter; Hunter, David
    Colour vision deficiency (CVD, colourblindness) is the failure or decreased ability to distinguish between certain colours even under normal lighting conditions. There are an estimated 300 million people worldwide with CVD, with approx. 1 in 12 men (8%) and 1 in 200 women (0.5%)
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    Exploring Language Pedagogy with Virtual Reality and Artificial Intelligence
    (The Eurographics Association, 2023) Michael, Brandon; Aburumman, Nadine; Vangorp, Peter; Hunter, David
    Virtual Reality (VR) is a highly immersive and interactive experience that renders users to be engrossed in a 3D virtual environment. The recent technological advancements with high-resolution headset display, and accurate tracking of six degrees of freedom paired with controllers allow life-like renditions of real-world scenarios as well as fictional scenarios without potential environmental risks. This paper explores the usage of Virtual Reality in education by incorporating current pedagogical approaches into an interactive 3D virtual environment. The focus of this study revolves around language pedagogy, in specific, the tool developed allows teach users fundamental Mandarin Chinese. This educational VR application enables users to practice their reading and writing skills through a calligraphy lesson and engages users in a listening and speaking lesson through natural conversation. To achieve an organic dialogue, phrases spoken by the user in a lesson are validated immediately through an intuitive phrase recognition system developed using machine learning. The developed prototype has undergone testing to ensure its efficacy. An initial investigation into this prototype found that the majority of participants were supportive of this concept and believe that it would improve the engagement of digital education.
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    Just Noticeable Difference of Dead Pixels in Monochrome Computer-Generated Holograms
    (The Eurographics Association, 2023) Lindfield, Nicholas; Carey, Remington; Hulusic, Vedad; Milne, Darran; Tang, Wen; Vangorp, Peter; Hunter, David
    Computer-generated holography (CGH) is a method for replicating scenes that incorporates depth, making them potentially much more realistic than traditional displays. Because CGH uses diffractive optics to generate scenes, holograms are also significantly more robust against dead pixels: while a single dead pixel is often noticeable in traditional displays, in holography much higher numbers are needed before a viewer realises the issue. This work is a pilot study to determine the Just Noticeable Difference of the number of dead pixels of a hologram, i.e., the minimum amount that need to be added before a viewer notices the difference. From these JNDs a quality ruler will be generated, which later work will use to compare the impact of other distortions on the perceived quality of a hologram. Results thus far suggest an addition of 4% dead pixels is required to notice a difference, which is significantly greater than the tolerance observed for traditional displays, where the fault class threshold is less than 0.05%.
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    An Image-based Model for 3D Shape Quality Measure
    (The Eurographics Association, 2023) Alhamazani, Fahd; Rosin, Paul L.; Lai, Yu-Kun; Vangorp, Peter; Hunter, David
    In light of increased research on 3D shapes and the increased processing capability of GPUs, there has been a significant increase in available 3D applications. In many applications, assessment of perceptual quality of 3D shapes is required. Due to the nature of 3D representation, this quality assessment may take various forms. While it is straightforward to measure geometric distortions directly on the 3D shape geometry, such measures are often inconsistent with human perception of quality. In most cases, human viewers tend to perceive 3D shapes from their 2D renderings. It is therefore plausible to measure shape quality using their 2D renderings. In this paper, we present an image-based quality metric for evaluating 3D shape quality given the original and distorted shapes. To provide a good coverage of 3D geometry from different views, we render each shape from 12 equally spaced views, along with a variety of rendering styles to capture different aspects of visual characteristics. Image-based metrics such as SSIM (Structure Similarity Index Measure) are then used to measure the quality of 3D shapes. Our experiments show that by effectively selecting a suitable combination of rendering styles and building a neural network based model, we achieve significantly better prediction for subjective perceptual quality than existing methods.
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    Intra-Model Smoothing Using Depth Aware Multi-Sample Anti-Aliasing for Deferred Rendering Pipelines
    (The Eurographics Association, 2023) Magnussen, Birk Martin; Vangorp, Peter; Hunter, David
    Subpixel geometry often causes lighting artifacts. In some cases, post-process anti-aliasing algorithms are not sufficiently able to smooth the resulting image. For forward rendering pipelines, multi-sample anti-aliasing is a powerful tool to avoid such artifacts. However, modern rendering pipelines commonly use deferred shading, which causes issues for multi-sample anti-aliasing. This article proposes a new method of combining a pipeline using deferred shading with multi-sample antialiasing while avoiding common pitfalls. The proposed method achieves this by intelligently resolving the geometry buffers with a custom shader based on the depth of samples. This allows the lighting shader to run unchanged on the geometry buffer on a per-fragment basis without additional performance costs. Furthermore, the proposed method is easy to retrofit to existing engines as no changes are required to either the model rendering shader or the deferred lighting shader. The proposed method is demonstrated and implemented on the example of the open-source game engine FreeSpace Open. It is shown that the proposed method is capable of preventing subpixel geometry artifacts, while also avoiding lighting artifacts from resolving geometry buffers and avoiding the performance overhead of calculating lighting per sample.