Computer Graphics & Visual Computing (CGVC) 2022

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https://diglib.eg.org/handle/10.2312/2633209

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    Interactive Visualisation of the Food Content of a Human Stomach in MRI
    (The Eurographics Association, 2022) Spann, Conor; Al-Maliki, Shatha; Boué, François; Lutton, Évelyne; Vidal, Franck; Peter Vangorp; Martin J. Turner
    Most medical imaging studies into human digestion focus on the organs themselves and neglect the content under digestion. Instead, analysing food inside digestive organs and any subsequent motion can provide valuable information about the digestive tract. This study is part of a larger project, with previous work done to automatically detect peas in a human stomach from MRI scans but it produced too many false positives. Our study therefore aims to accurately visualise peas in a human stomach whilst also providing facilities to correct the mistakes made by the previous pea detection. Our solution is a visualisation and correction tool split into 2D and 3D visualisation areas. The 2D areas show three sequential stomach slices with detected peas as green circles and allows the user to correct the pea detection. Peas can be added, removed or marked as unsure. The 3D area shows a Marching Cubes rendering of the stomach with spherical glyphs as the peas. Due to the way the data was acquired, some pea motion was also visualised. Aside from difficulties interpreting the data due to acquisition artefacts, our tool was found to be very easy to use, with some minor improvement suggestions for interacting with the images. Overall, the software achieved its aims of visualising the peas and stomach whilst also providing methods to correct the pea data. Future work will look into improving the pea detection and more work into following the pea motion.
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    Semi-Sharp Subdivision Shading
    (The Eurographics Association, 2022) Zhou, Jun; Boonstra, Jan; Kosinka, Jirí; Peter Vangorp; Martin J. Turner
    Subdivision is a method for generating a limit surface from a coarse mesh by recursively dividing its faces into several smaller faces. This process leads to smooth surfaces, but often suffers from shading artifacts near extraordinary points due to the lower quality of the normal field there. The idea of subdivision shading is to apply the same subdivision rules that are used to subdivide geometry to also subdivide the normals associated with mesh vertices. This leads to smoother normal fields, which in turn removes the shading artifacts. However, the original subdivision shading method does not support sharp and semi-sharp creases, which are important ingredients in subdivision surface modelling. We present two approaches to extending subdivision shading to work also on models with (semi-)sharp creases.
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    Computer Graphics and Visual Computing (CGVC): Frontmatter
    (The Eurographics Association, 2022) Peter Vangorp; Martin J. Turner; Peter Vangorp; Martin J. Turner
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    Real-time Indexing of Point Cloud Data During LiDAR Capture
    (The Eurographics Association, 2022) Bormann, Pascal; Dorra, Tobias; Stahl, Bastian; Fellner, Dieter W.; Peter Vangorp; Martin J. Turner
    We introduce a software system that is capable of indexing point cloud data in real-time as it is being captured by a LiDAR (Light Detection and Ranging) sensor. Our system extends the popular MNO (modifiable nested octree) structure so that it can be built progressively without knowing the bounding box of the point cloud. Using a task-based parallel algorithm incoming points are continuously processed and distributed to the octree nodes using grid-based sampling. Different task priority functions enable prioritization of either high point throughput or low latency. We provide a reference implementation of this system and evaluate it using both a synthetic and a real-world test scenario. The synthetic test demonstrates good scalability up to 16 threads, with maximum point throughputs of up to 1.8 million points per second. These numbers are verified on a sensor system using a Velodyne VLP-16 LiDAR sensor, where our system is able to index all data produced by the scanner in real-time.
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    Towards Developing a Digital application for the Five Design-Sheets Methodology
    (The Eurographics Association, 2022) Owen, Aron E.; Roberts, Jonathan C.; Peter Vangorp; Martin J. Turner
    The Five Design-Sheet Methodology is a sketching methodology that helps people ideate different designs; it has been used to develop computer interfaces, games and data visualisations. Traditionally, it is a paper-based process that structures the developer to think about their design solution over five sheets with five sections. However, with the rise of mobile phones and tablets, there is an emerging opportunity to achieve the sketched design ideation process in a digital form. This work investigates the transition of the Five Design-Sheets from a paper-based methodology into a digital sketching application. The paper introduces how we considered the challenge, and have started to develop an application. Currently our application implements the first sheet of the FdS process. We describe the application and present a brief evaluation of the work with designers and developers.
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    Personalised Authentic assessments with Synchronous Learning Activities: a Framework for Teaching Visualisation and Graphics
    (The Eurographics Association, 2022) Roberts, Jonathan C.; Peter Vangorp; Martin J. Turner
    We present an activities framework for learning visualisation and computer graphics. The framework pivots around the academic developing an authentic learning scenario that is personalised for every student, followed by a suite of synchronous learning activities. The authentic assessment helps set the scene and motivate the learners, activities bring the students together to work on an aligned sub-task, while personalising the task enables each student to discuss their work without worrying about plagiarism. We demonstrate how we have applied the structure in two modules; first a third-year degree level module in computer graphics rendering and second an information visualisation masters module. In this paper we present the framework and discuss our experience with using it.
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    Developing Transitional Activities to Support Student Transition to University: Findings From a Qualitative Co-design Study With University Stakeholders
    (The Eurographics Association, 2022) Threlfall, Danielle; Headleand, Christopher J.; Hicks, Kieran; Miller, Kirsty; Peter Vangorp; Martin J. Turner
    This study utilised a co-design approach to actively engage university stakeholders to explore the challenges of students through the transition to university. The feedback gathered from participants revealed that key transitional issues for students included managing their finances, understanding support services available, and familiarisation with campus navigation. Participants created activities to support these challenges, which, in a future stage, will be added to the Lincoln Island Project, a game being used to determine whether a video game can be used to support students during the transition to university.
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    Augmented Reality for Safety Zones in Human-Robot Collaboration
    (The Eurographics Association, 2022) Cogurcu, Yunus Emre; Douthwaite, James A.; Maddock, Steve; Peter Vangorp; Martin J. Turner
    Worker productivity in manufacturing could be increased by reducing the distance between robots and humans in human-robot collaboration (HRC). However, physical cages generally limit this interaction. We use Augmented Reality (AR) to visualise virtual safety zones on a real robot arm, thereby replacing the physical cages and bringing humans and robots closer together. We demonstrate this with a collaborative pick and place application that makes use of a Universal Robots 10 (UR10) robot arm and a Microsoft HoloLens 2 for control and visualisation. This mimics a real task in an industrial robot cell. The virtual safety zone sizes are based on ISO standards for HRC. However, we are the first to also consider hardware and network latencies in the calculations of the virtual safety zone sizes.
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    Chladni Plate Visualisation
    (The Eurographics Association, 2022) Dashti, Sarah; Prakash, Edmond; Navarro-Newball, Andres Adolfo; Hussain, Fiaz; Carroll, Fiona; Peter Vangorp; Martin J. Turner
    The creation of images made out of sound is an ancient discovery from many civilisations, called Cymatics. Cymatics can be referred to as the science of visualising audio frequencies through the Chladni plate. Over the past several years, many scientists, artists and designers have tried to visually and physically represent sound. Physicalising sound was through using liquids and particles as a medium with sound energy to deform and reform the medium aesthetically, creating a unique texture. In the visual arts of computer graphics, the texture is the perceived surface quality showing details of the surface model and colour. The use of texture in computer graphics for modelling and gaming industries is still growing, opening new possibilities for new complex textures yet simple to apply. The paper explores methods of integrating art and science, showing the practices of contemporary Chladni visualisation from an artist's perspective in 3D modelling. The paper also introduces the technique of using computer graphics to compare procedural textures with Chladni's plate representing visual aspects of our novel approach.
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    Meshing of Spiny Neuronal Morphologies using Union Operators
    (The Eurographics Association, 2022) Abdellah, Marwan; Cantero, Juan José García; Foni, Alessandro; Guerrero, Nadir Román; Boci, Elvis; Schürmann, Felix; Peter Vangorp; Martin J. Turner
    Neurons are characterized by thin and long interleaving arborizations in which creating accurate mesh models of their cellular membranes is challenging. While union operators are central for CAD/CAM modeling and computer graphics applications, their applicability to neuronal mesh generation has not been explored. In this work, we present the results of exploring the effectiveness of using union operators to generate high fidelity surface meshes of spiny neurons from their morphological traces. To improve the visual realism of the resulting models, a plausible shape of the cell body is also realized with implicit surfaces (metaballs). The algorithm is implemented in Blender based on its Python API and is integrated into NeuroMorphoVis, a neuroscience-specific framework for visualization and analysis of neuronal morphologies. Our method is applied to a dataset consisting of more than 600 neurons representing 60 morphological types reconstructed from the neocortex of a juvenile rat. The performance of our implementation is quantitatively analyzed, and the results are qualitatively compared to previous implementation. The resulting meshes are applicable in multiple contexts including visualization and analysis of full compartmental simulations and generation of high quality multimedia content for scientific visualization and visual computing (Figure 1).
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    Building Augmented and Virtual Reality Experiences for Children with Visual Diversity
    (The Eurographics Association, 2022) Navarro-Newball, Andres Adolfo; Galvis, Martín Vladimir Alonso Sierra; Martínez, Juan Carlos; Betancourt, Juan José; Ramirez, Katherine; Velasquez, Andrés; Quinto, Valeria; Restrepo, Gerardo; Castillo, Andrés Darío; Asprilla, Elizabeth; Portilla, Anita; Serrano, Laura Lucia; Rodríguez, Frank Alexander; Peñaloza, Eliana; Peter Vangorp; Martin J. Turner
    Currently, a binational network of universities carries out a collaborative project which seeks to promote inclusion and education in environmental issues for children. The so-called ''Colombia-Québec collaborative project'' seeks to develop interactive narratives about four Colombian animals to help develop language, cognitive and motricity skills in children while they gain awareness of endangered animals. Chosen animals include the cotton top tamarin, the jaguar, the spectacled bear, and the condor. We are building several interactive systems which take advantage of augmented and virtual reality technologies to expand narratives developed by speech and language therapists. Our goal is to use these systems to study the effects of the virtuality continuum in visually diverse children's development. We present our advances towards achieving it.
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    Extended Reality (XR) Immersive Visualisation: Identifying AI project member 'needs' in order to design for a more effective Low-Code Machine Learning Model Development experience
    (The Eurographics Association, 2022) Wheeler, Richard; Carroll, Fiona; Peter Vangorp; Martin J. Turner
    With organisations making machine learning projects more of a priority, issues have been found regarding the presentation of these types of projects and in particular, in explaining how the models that are produced work, not only internally but also to the final user. The following paper discusses the design and development of a novel Extended Reality (XR) solution that enables rapid development, experimentation and clear presentation of complex machine learning models using eXplainable AI (XAI) principles. The paper documents the findings from a short initial feasibility questionnaire study which probed participant's opinions around their current use of XR environments, low-code development platforms, and their experience of working on machine learning model development projects. The findings of that study showed that the proposed solution could be deemed novel especially regarding its use of extended reality, as none of the participants had used this technology for machine learning development productivity or collaboration. The aim of the paper is to highlight the development of a system that uses a low-code development platform for the development of machine learning models and then uses an extended reality environment to not only enable collaboration within development teams but also as a system for presenting a model's output. This paper documents the early phases of the research process (i.e. identifying the need) whilst also sharing ideas on how the issue can be solved.
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    Depth-aware Neural Style Transfer using Instance Normalization
    (The Eurographics Association, 2022) Ioannou, Eleftherios; Maddock, Steve; Peter Vangorp; Martin J. Turner
    Neural Style Transfer (NST) is concerned with the artistic stylization of visual media. It can be described as the process of transferring the style of an artistic image onto an ordinary photograph. Recently, a number of studies have considered the enhancement of the depth-preserving capabilities of the NST algorithms to address the undesired effects that occur when the input content images include numerous objects at various depths. Our approach uses a deep residual convolutional network with instance normalization layers that utilizes an advanced depth prediction network to integrate depth preservation as an additional loss function to content and style. We demonstrate results that are effective in retaining the depth and global structure of content images. Three different evaluation processes show that our system is capable of preserving the structure of the stylized results while exhibiting style-capture capabilities and aesthetic qualities comparable or superior to state-of-the-art methods. Project page: https://ioannoue.github.io/depth-aware-nst-using-in.html.
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    Parallelizing Rendering on Devices with Multi-Core CPUs - Implementation Suggestion for Education
    (The Eurographics Association, 2022) Porath, Ron; Peter Vangorp; Martin J. Turner
    It is a well-known fact that parallelizing rendering calculations in ray tracing programs is possible and useful in many use cases, because the calculation for each pixel is often independent of the calculation of other pixels. This is also one main reason for the massive performance gain on GPUs and allows real-time rendering. However, it is often too difficult to teach students at schools and universities on how to program GPUs and parallelized rendering or it goes beyond the scope of the course. In order to still provide them a feasible way to make use of parallel rendering on their devices, be it mobile phones, tablets or PCs, we describe in this paper an implementation method, which does not require a deep IT knowledge and can be taught and applied easily. The implementation method is based on JavaScript, which became one of the easiest languages to learn programming, and is therefore often used as a great educational tool to teach and learn the basics of 3D Graphics and Rendering as well as physics, mathematics and programming. The method described in this article allows the distribution of computations to all CPU cores in modern devices, and demonstrates shorter rendering calculation times up to 70-85%.