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Item Recreational Motion Simulation: A New Frontier for Virtual Worlds Research(The Eurographics Association, 2021) Williams, Benjamin; Headleand, Christopher J.; Xu, Kai and Turner, MartinMotion 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.Item Recognising Specific Foods in MRI Scans Using CNN and Visualisation(The Eurographics Association, 2020) Gardner, Joshua; Al-Maliki, Shatha; Lutton, Évelyne; Boué, François; Vidal, Franck; Ritsos, Panagiotis D. and Xu, KaiThis work is part of an experimental project aiming at understanding the kinetics of human gastric emptying. For this purpose magnetic resonance imaging (MRI) images of the stomach of healthy volunteers have been acquired using a state-of-art scanner with an adapted protocol. The challenge is to follow the stomach content (food) in the data. Frozen garden peas and petits pois have been chosen as experimental proof-of-concept as their shapes are well defined and are not altered in the early stages of digestion. The food recognition is performed as a binary classification implemented using a deep convolutional neural network (CNN). Input hyperparameters, here image size and number of epochs, were exhaustively evaluated to identify the combination of parameters that produces the best classification. The results have been analysed using interactive visualisation. We prove in this paper that advances in computer vision and machine learning can be deployed to automatically label the content of the stomach even when the amount of training data is low and the data imbalanced. Interactive visualisation helps identify the most effective combinations of hyperparameters to maximise accuracy, precision, recall and F1 score, leaving the end-user evaluate the possible trade-off between these metrics. Food recognition in MRI scans through neural network produced an accuracy of 0.97, precision of 0.91, recall of 0.86 and F1 score of 0.89, all close to 1.Item Medical Ultrasound Training in Virtual Reality(The Eurographics Association, 2020) Elliman, James P.; Bethapudi, Sarath; Koulieris, George Alex; Ritsos, Panagiotis D. and Xu, KaiIn this work we propose a novel training solution for learning and practising the core psychomotor skills required in Diagnostic Ultrasound examinations with a computer-based simulator. This is in response to the long-standing challenges faced by educators in providing regular training opportunities as a shortage of equipment, staff unavailability and cost, hamper the current training model. We propose an alternative, VR-based model with a highly realistic 3D environment. To further realism of the experience, 3D printed props that work in conjunction with the simulation software will be designed. Our approach further extends previous work in generative model-based US simulation by developing a ray-tracing algorithm for use with the recently released NVidia RTX technology.Item Projectional Radiography Simulator: an Interactive Teaching Tool(The Eurographics Association, 2019) Sujar, Aaron; Kelly, Graham; García, Marcos; Vidal, Franck; Vidal, Franck P. and Tam, Gary K. L. and Roberts, Jonathan C.Radiographers need to know a broad range of knowledge about X-ray radiography, which can be specific to each part of the body. Due to the harmfulness of the ionising radiation used, teaching and training using real patients is not ethical. Students have limited access to real X-ray rooms and anatomic phantoms during their studies. Books, and now web apps, containing a set of static pictures are then often used to illustrate clinical cases. In this study, we have built an Interactive X-ray Projectional Simulator using a deformation algorithm with a real-time X-ray image simulator. Users can load various anatomic models and the tool enables virtual model positioning in order to set a specific position and see the corresponding X-ray image. It allows teachers to simulate any particular X-ray projection in a lecturing environment without using real patients and avoiding any kind of radiation risk. This tool also allows the students to reproduce the important parameters of a real X-ray machine in a safe environment. We have performed a face and content validation in which our tool proves to be realistic (72% of the participants agreed that the simulations are visually realistic), useful (67%) and suitable (78%) for teaching X-ray radiography.Item Optimising Underwater Environments for Mobile VR(The Eurographics Association, 2019) Cenydd, Llyr ap; Headleand, Christopher; Vidal, Franck P. and Tam, Gary K. L. and Roberts, Jonathan C.Mobile Virtual Reality (VR) has advanced considerably in the last few years, driven by advances in smartphone technology. There are now a number of commercial offerings available, from smartphone powered headsets to standalone units with full positional tracking. Similarly best practices in VR have matured quickly, facilitating comfortable and immersive VR experiences. There remains however many optimisation challenges when working with these devices, as while the need to render at high frame rates is universal, the hardware is limited by both computational power and battery capacity. There is also often a requirement that apps run smoothly across a wide variety of headsets. In this paper, we describe lessons learned in rendering and optimising underwater environments for mobile VR, based on our experience developing the popular aquatic safari application 'Ocean Rift'. We start by analyzing essential best practices for mobile app development, before describing low-cost techniques for creating immersive underwater environments. While some techniques discussed are universal to modern mobile VR development, we also consider issues that are unique to underwater applications.Item Improving Ray Tracing Performance with Variable Rate Shading(The Eurographics Association, 2021) Dahlin, Alexander; Sundstedt, Veronica; Xu, Kai and Turner, MartinHardware-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.Item Where's Wally? A Machine Learning Approach(The Eurographics Association, 2021) Barthelmes, Tobias; Vidal, Franck; Xu, Kai and Turner, MartinObject 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.Item CLAWS: Computational Load Balancing for Accelerated Neighbor Processing on GPUs using Warp Scheduling(The Eurographics Association, 2020) Gross, Julian; Köster, Marcel; Krüger, Antonio; Ritsos, Panagiotis D. and Xu, KaiNearest neighbor search algorithms on GPUs have been improving for years. Starting with tree-based approaches in the middle 70's, state-of-the-art methods use hash-based or grid-based methods. Leveraging high-performance hardware functionality decreases runtime of these search algorithms. Furthermore, memory consumption has been decreased significantly as well using Shared Memory. In the scope of these enhancements, particles have been reordered by different constraints that simplify neighbor processing. However, inspecting the existing algorithms reveals underused capabilities caused by algorithm desing. Exploiting these capabilities in a smart way can increase occupancy and efficiency on GPUs. In this paper, we present a neighbor processing approach that is based on dynamic load balancing. We rely on a lightweight workload-analysis phase that is applied during neighbor processing to distribute work throughout all warps in a thread group on-the-fly. In different domains, the neighbor function is often symmetric and, thus, commutative in each argument. In contrast to prior work, we use this domain knowledge to reduce the number of memory accesses considerably. Measurements of the newly introduced features on our evaluation scenarios show a comparable runtime performance to state-of-the-art methods. Increasing the overall workload by processing million-particle domains leads to significant improvements in terms of runtime. At the same time, we minimize global memory consumption to enable more particles to be processed compared to current approaches.Item Colour Processing in Adversarial Attacks on Face Liveness Systems(The Eurographics Association, 2019) Abduh, Latifah; Ivrissimtzis, Ioannis; Vidal, Franck P. and Tam, Gary K. L. and Roberts, Jonathan C.In the context of face recognition systems, liveness test is a binary classification task aiming at distinguishing between input images that come from real people's faces and input images that come from photos or videos of those faces, and presented to the system's camera by an attacker. In this paper, we train the state-of-the-art, general purpose deep neural network ResNet for liveness testing, and measure the effect on its performance of adversarial attacks based on the manipulation of the saturation component of the imposter images. Our findings suggest that higher saturation values in the imposter images lead to a decrease in the network's performance. Next, we study the relationship between the proposed adversarial attacks and corresponding direct presentation attacks. Initial results on a small dataset of processed images which are then printed on paper or displayed on an LCD or a mobile phone screen, show that higher saturation values lead to higher values in the network's loss function, indicating that these colour manipulation techniques can indeed be converted into enhanced presentation attacks.Item Breathing Life into Statues Using Augmented Reality(The Eurographics Association, 2020) Ioannou, Eleftherios; Maddock, Steve; Ritsos, Panagiotis D. and Xu, KaiAR art is a relatively recent phenomenon, one that brings innovation in the way that artworks can be produced and presented in real-world locations and environments. We present an AR art app, running in real time on a smartphone, that can be used to bring to life inanimate objects such as statues. The work relies on a virtual copy of the real object, which is produced using photogrammetry, as well as a skeleton rig for subsequent animation. As part of the work, we present a new diminishing reality technique, based on the use of particle systems, to make the real object 'disappear' and be replaced by the animating virtual copy, effectively animating the inanimate. The approach is demonstrated on two objects: a juice carton and a small giraffe sculpture.