Perception-Based Techniques to Enhance User Experience in Virtual Reality

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2024-07-26
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Virtual reality (VR) ushered in a new era of immersive content viewing with vast potential for entertainment, design, medicine, and other fields. However, the willingness of users to practically apply the technology is bound to the quality of the virtual experience. In this dissertation, we describe the development and investigation of novel techniques to reduce negative influences on the user experience in VR applications. Our methods not only include substantial technical improvements but also consider important characteristics of human perception that are exploited to make the applications more effective and subtle. Mostly, we are focused on visual perception, since we deal with visual stimuli, but we also consider the vestibular sense which is a key component for the occurrence of negative symptoms in VR, referred to as cybersickness. In this dissertation, our techniques are designed for three groups of VR applications, characterized by the degree of freedom to apply adjustments. The first set of techniques addresses the extension of VR systems with stimulation hardware. By adjusting common techniques from the medical field, we artificially induce human body signals to create immersive experiences that reduce common mismatches between perceptual information. The second group focuses on applications that use common hardware and allow adjustments of the full render pipeline. Here, especially immersive video content is notable, where the frame rates and quality of the presentations are often not in line with the high requirements of VR systems to satisfy a decent user experience. To address the display problems, we present a novel video codec based on wavelet compression and perceptual features of the visual system. Finally, the third group of applications is the most restrictive and does not allow modifications of the rendering pipeline. Here, our techniques consist of post-processing manipulations in screen space after rendering the image, without knowledge of the 3D scene. To allow techniques in this group to be subtle, we exploit fundamental properties of human peripheral vision and apply spatial masking as well as gaze-contingent motion scaling in our methods.
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