Computer Graphics & Visual Computing (CGVC) 2021

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https://diglib.eg.org/handle/10.2312/2633082

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Browsing Computer Graphics & Visual Computing (CGVC) 2021 by Subject "Computing methodologies"

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    3D Visualisations Should Not be Displayed Alone - Encouraging a Need for Multivocality in Visualisation
    (The Eurographics Association, 2021) Roberts, Jonathan C.; Mearman, Joseph W.; Butcher, Peter W. S.; Al-Maneea, Hayder M.; Ritsos, Panagiotis D.; Xu, Kai and Turner, Martin
    We believe that 3D visualisations should not be used alone; by coincidentally displaying alternative views the user can gain the best understanding of all situations. The different presentations signify manifold meanings and afford different tasks. Natural 3D worlds implicitly tell many stories. For instance, walking into a living room, seeing the TV, types of magazines, pictures on the wall, tells us much about the occupiers: their occupation, standards of living, taste in design, whether they have kids, and so on. How can we similarly create rich and diverse 3D visualisation presentations? How can we create visualisations that allow people to understand different stories from the data? In a multivariate 2D visualisation a developer may coordinate and link many views together to provide exploratory visualisation functionality. But how can this be achieved in 3D and in immersive visualisations? Different visualisation types, each have specific uses, and each has the potential to tell or evoke a different story. Through several use-cases, we discuss challenges of 3D visualisation, and present our argument for concurrent and coordinated visualisations of alternative styles, and encourage developers to consider using alternative representations with any 3D view, even if that view is displayed in a virtual, augmented or mixed reality setup.
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    Design Guidelines for Virtual Neurological Procedures
    (The Eurographics Association, 2021) Mancosu, Mattia S.; Czanner, Silvester; Xu, Kai and Turner, Martin
    The role of technology has become more and more preponderant for educational purposes in schools, in universities and for training. It is also applied in healthcare and neurology training thanks to the proven effectiveness and the rising demand inside hospitals and medical schools. The necessity to outline design guidelines is increasing hand to hand with the aforementioned phenomenon. In this paper we will discuss some key aspects of a healthcare teaching application such as the fidelity of the learning environment, the target platform of the application with a particular focus on Virtual Reality, and the learning strategies that can be implemented within the program. We will also illustrate some results of our stroke assessment training application, where we proved the effectiveness of the proper implementation of some design aspects that we addressed inside the guidelines section.
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    Improving Ray Tracing Performance with Variable Rate Shading
    (The Eurographics Association, 2021) Dahlin, Alexander; Sundstedt, Veronica; Xu, Kai and Turner, Martin
    Hardware-accelerated ray tracing has enabled ray traced reflections for real-time applications such as games. However, the number of traced rays during each frame must be kept low to achieve expected frame rates. Therefore, techniques such as rendering the reflections at quarter resolution are used to limit the number of rays. The recent hardware features inline ray tracing, and variable rate shading (VRS) could be combined to limit the number of rays even further. This research aims to use hardware VRS to limit the number of rays while maintaining the visual quality in the final rendered image. An experiment with performance tests is performed on a rendering pipeline using different techniques to generate rays. The techniques use inline ray tracing combined with VRS and ray generation shaders. These are compared and evaluated using performance tests and the image evaluator FLIP. The results show that limiting the number of rays with hardware VRS leads to improved performance while the difference in visual quality remains comparable.
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    Learning Activities in Colours and Rainbows for Programming Skill Development
    (The Eurographics Association, 2021) Roberts, Jonathan C.; Xu, Kai and Turner, Martin
    We present how we have created a series of bilingual (English and Welsh) STEM activities focusing on rainbows, colours, light and optical effects. The activities were motivated by the many rainbows that appeared in windows in the UK, in support of the National Health Service at the start of the coronavirus pandemic. Rainbows are hopeful and are very fitting to be used as a positive iconic image at a time of much uncertainty. In this paper we explain how we have developed and organised the activities, focusing on colours, computer graphics and computer programming. Each lesson contains one or more activities, which enable people to take an active role in their learning.We have carefully prepared and organised several processes to guide academic colleagues to create and publish different activities in the theme. Which means that the activities appear similarly structured, can be categorised and searched in a consistent way. This structure can act as a blueprint for others to follow and apply to develop their own online course. The activities incrementally take people through learning about colour, rainbows, planning what to program, design and strategies to create colourful pictures using simple computer graphics principles based in processing.org.
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    RECCS: Real-Time Camera Control for Particle Systems
    (The Eurographics Association, 2021) Köster, Marcel; Groß, Julian; Krüger, Antonio; Xu, Kai and Turner, Martin
    Interactive exploration and analysis of large 3D particle systems, consisting of hundreds of thousands of particles, are common tasks in the field of scientific and information visualization. These steps typically involve selection and camera-update operations in order to reveal patterns or to focus on subsets. Moreover, if a certain region is known to be potentially interesting or a selection has been made, the user will have to choose a proper camera setup to investigate further. However, such a setup is typically chosen in a way that the interesting region is in the center of the screen. Unfortunately, it still needs to show important characteristics of the selected subset and has the least amount of occlusions with respect to other particles but shows enough context information in terms of non-selected particles. In this paper, we propose a novel method for real-time camera control in 3D particle systems that fulfills these requirements. It is based on a user and/or domain-specific evaluation heuristic and parallel optimization algorithm that is designed for Graphics-Processing Units (GPUs). In addition, our approach takes only several milliseconds to complete, even on the aforementioned large datasets while consuming only a few megabytes in global GPU memory in general. This is due the fact that we are able to reduce the processing complexity significantly using screenspace information and the excessive use of fast on-chip shared memory. This allows it to be seamlessly integrated into modern visualization systems that need real-time feedback while processing large particle-based datasets.
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    Recreational Motion Simulation: A New Frontier for Virtual Worlds Research
    (The Eurographics Association, 2021) Williams, Benjamin; Headleand, Christopher J.; Xu, Kai and Turner, Martin
    Motion simulation is a developing field which continues to grow with the recent incline in commercial virtual reality. Whilst the majority of motion simulation research focuses on flight simulation and training, its utility in recreational settings is often overlooked. Despite this lack of research, the use of motion simulators for recreational purposes spans decades, and is still today one of the most popular applications of motion simulator devices. Furthermore, with the recent development of low-cost motion simulation platforms, consumers have begun to use these devices in the home. Research regarding motion simulation and its effects in recreational experiences is needed now more than ever, and in this position paper we outline several reasons for its importance.
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    Training Dataset Construction for Anomaly Detection in Face Anti-spoofing
    (The Eurographics Association, 2021) Abduh, Latifah; Ivrissimtzis, Ioannis; Xu, Kai and Turner, Martin
    Anomaly detection, which is approaching the problem of face anti-spoofing as a one-class classification problem, is emerging as an increasingly popular alternative to the traditional approach of training binary classifiers on specialized anti-spoofing databases which contain both client and imposter samples. In this paper, we discuss the training protocols in the existing work on anomaly detection for face anti-spoofing, and note that they use images exclusively from specialized anti-spoofing databases, even though only common images of real faces are needed. In a proof-of-concept experiment, we demonstrate the potential benefits of adding in the anomaly detection training sets images from general face recognition, rather than specialised face anti-spoofing, databases, or images from the in-the-wild images. We train a convolutional autoencoder on real faces and compare the reconstruction error against a threshold to classify a face image as either client or imposter. Our results show that the inclusion in the training set of in-the-wild images increases the discriminating power of the classifier on an unseen database, as evidenced by an increase in the value of the Area Under the Curve.
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    Where's Wally? A Machine Learning Approach
    (The Eurographics Association, 2021) Barthelmes, Tobias; Vidal, Franck; Xu, Kai and Turner, Martin
    Object detection has been implemented in all sorts of real-life scenarios such as facial recognition, traffic monitoring and medical imaging but the research that has gone into object detection in drawings and cartoons is not nearly as extensive. The Where's Wally puzzle books give a good opportunity to implement some of these real-life methods into the fictional world. The Wally detection framework proposed is composed of two stages: i) a Haar-cascade classifier based on the Viola-Jones framework, which detects possible candidates from a scenario from the Where'sWally books, and ii) a lightweight convolutional neural network (CNN) that re-labels the objects detected by the cascade classifier. The cascade classifier was trained on 85 positive images and 172 negative images. It was then applied to 12 test images, which produced over 400 false positives. To increase the accuracy of the models, hard negative mining was implemented. The framework achieved a recall score of 84.61% and an F1 score of 78.54%. Improvements could be made to the training data or the CNN to further increase these scores.