TOWARDS EFFECTIVE DISPLAYS FOR VIRTUAL AND AUGMENTED REALITY

Virtual and augmented reality (VR and AR) are becoming increasingly accessible and useful nowadays. This dissertation focuses on several aspects of designing effective displays for VR and AR. Compared to conventional desktop displays, VR and AR displays can better engage the human peripheral vision. This provides an opportunity for more information to be perceived. To fully leverage the human visual system, we need to take into account how the human visual system perceives things differently in the periphery than in the fovea. By investigating the relationship of the perception time and eccentricity, we deduce a scaling function which facilitates content in the far periphery to be perceived as efficiently as in the central vision. AR overlays additional information on the real environment. This is useful in a number of fields, including surgery, where time-critical information is key. We present our medical AR system that visualizes the occluded catheter in the external ventricular drainage (EVD) procedure. We develop an accurate and efficient catheter tracking method that requires minimal changes to the existing medical equipment. The AR display projects a virtual image of the catheter overlaid on the occluded real catheter to depict its real-time position. Our system can make the risky EVD procedure much safer. Existing VR and AR displays support a limited number of focal distances, leading to vergence-accommodation conflict. Holographic displays can address this issue. In this dissertation, we explore the design and development of nanophotonic phased array (NPA) as a special class of holographic displays. NPAs have the advantage of being compact and support very high refresh rates. However, the use of the thermo-optic effect for phase modulation renders them susceptible to the thermal proximity effect. We study how the proximity effect impacts the images formed on NPAs. We then propose several novel algorithms to compensate for the thermal proximity effect on NPAs and compare their effectiveness and computational efficiency. Computer-generated holography (CGH) has traditionally focused on 2D images and 3D images in the form of meshes and point clouds. However, volumetric data can also benefit from CGH. One of the challenges in the use of volumetric data sources in CGH is the computational complexity needed to calculate the holograms of volumetric data. We propose a new method that achieves a significant speedup compared to existing holographic volume rendering methods

Enhancing Visual and Gestural Fidelity for Effective Virtual Environments

A challenge for the virtual reality (VR) industry is facing is that VR is not immersive enough to make people feel a genuine sense of presence: the low frame rate leads to dizziness and the lack of human body visualization limits the human-computer interaction. In this dissertation, I present our research on enhancing visual and gestural fidelity in the virtual environment. First, I present a new foveated rendering technique: Kernel Foveated Rendering (KFR), which parameterizes foveated rendering by embedding polynomial kernel functions in log-polar space. This GPU-driven technique uses parameterized foveation that mimics the distribution of photoreceptors in the human retina. I present a two-pass kernel foveated rendering pipeline that maps well onto modern GPUs. I have carried out user studies to empirically identify the KFR parameters and have observed a 2.8x-3.2x speedup in rendering on 4K displays. Second, I explore the rendering acceleration through foveation for 4D light fields, which captures both the spatial and angular rays, thus enabling free-viewpoint rendering and custom selection of the focal plane. I optimize the KFR algorithm by adjusting the weight of each slice in the light field, so that it automatically selects the optimal foveation parameters for different images according to the gaze position. I have validated our approach on the rendering of light fields by carrying out both quantitative experiments and user studies. Our method achieves speedups of 3.47x-7.28x for different levels of foveation and different rendering resolutions. Thirdly, I present a simple yet effective technique for further reducing the cost of foveated rendering by leveraging ocular dominance - the tendency of the human visual system to prefer scene perception from one eye over the other. Our new approach, eye-dominance-guided foveated rendering (EFR), renders the scene at a lower foveation level (with higher detail) for the dominant eye than the non-dominant eye. Compared with traditional foveated rendering, EFR can be expected to provide superior rendering performance while preserving the same level of perceived visual quality. Finally, I present an approach to use an end-to-end convolutional neural network, which consists of a concatenation of an encoder and a decoder, to reconstruct a 3D model of a human hand from a single RGB image. Previous research work on hand mesh reconstruction suffers from the lack of training data. To train networks with full supervision, we fit a parametric hand model to 3D annotations, and we train the networks with the RGB image with the fitted parametric model as the supervision. Our approach leads to significantly improved quality compared to state-of-the-art hand mesh reconstruction techniques

Mobile depth sensing technology and algorithms with application to occupational therapy healthcare

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe UK government is striving to shift its current healthcare delivery model from clini-cian–oriented services, to that of patient and self–care–oriented intervention strategies. It seeks to do so through Information Communication (ICT) and Computer Mediated Re-ality Technologies (CMRT) as a key strategy to overcome the ever–increasing scarcity of healthcare resources and costs. To this end, in the UK the use of paper–based information systems have exhibited their limitations in providing apposite care. At the national level, The Royal College of Occupational Therapists (RCOT) identify home visits and modifica-tions as key levers in a multifactorial health programme to evaluate interventions for older people with a history of falling or are identified as being prone to falling. Prescribing Assistive Equipment (AE) is one such mechanism that seeks to reduce the risk of falling whilst promoting the continued independence of physical dexterity and mobility in older adults at home. In the UK, the yearly cost of falls is estimated at £2.3 billion. Further evidence places a 30% to 60% abandonment rate on prescribed AE by and large due to a ‘poor fit’ and measurement inaccuracies. To remain aligned with the national strategy, and assist in the eradication of measurement inaccuracies, this thesis employs Mobile Depth Sensing and Motion Track-ing Devices (MDSMTDs) to assist OTs in in the process of digitally measuring the extrin-sic fall–risk factors for the provision of AE. The quintessential component in this assess-ment lies in the measurement of fittings and furniture items in the home. To digitise and aid in this process, the artefact presented in this thesis employs stereo computer–vision and camera calibration algorithms to extract edges in 3D space. It modifies the Sobel–Feldman convolution filter by reducing the magnitude response and employs the camera intrinsic parameters as a mechanism to calculate the distortion matrix for interpolation between the edges and the 3D point cloud. Further Augmented Reality User Experience (AR-UX) facets are provided to digitise current state of the art clinical guidance and over-lay its instructions onto the real world (i.e., 3D space). Empirical mixed methods assessment revealed that in terms of accuracy, the arte-fact exhibited enhanced performance gains over current paper–based guidance. In terms of accuracy consistency, the artefact can rectify measurement consistency inaccuracies, but there are still a wide range of factors that can influence the integrity of the point-cloud in respect of the device’s point-of-view, holding positions and measurement speed. To this end, OTs usability, and adoption preferences materialise in favour of the artefact. In conclusion, this thesis demonstrates that MDSMTDs are a promising alterna-tive to existing paper–based measurement practices as OTs appear to prefer the digital–based system and that they can take measurements more efficiently and accurately