Inattentional Blindness for Redirected Walking Using Dynamic Foveated Rendering

Redirected walking is a Virtual Reality(VR) locomotion technique which enables users to navigate virtual environments (VEs) that are spatially larger than the available physical tracked space. In this work we present a novel technique for redirected walking in VR based on the psychological phenomenon of inattentional blindness. Based on the user's visual fixation points we divide the user's view into zones. Spatially-varying rotations are applied according to the zone's importance and are rendered using foveated rendering. Our technique is real-time and applicable to small and large physical spaces. Furthermore, the proposed technique does not require the use of stimulated saccades but rather takes advantage of naturally occurring saccades and blinks for a complete refresh of the framebuffer. We performed extensive testing and present the analysis of the results of three user studies conducted for the evaluation

Towards Understanding and Expanding Locomotion in Physical and Virtual Realities

Among many virtual reality interactions, the locomotion dilemma remains a significant impediment to achieving an ideal immersive experience. The physical limitations of tracked space make it impossible to naturally explore theoretically boundless virtual environments with a one-to-one mapping. Synthetic techniques like teleportation and flying often induce simulator sickness and break the sense of presence. Therefore, natural walking is the most favored form of locomotion. Redirected walking offers a more natural and intuitive way for users to navigate vast virtual spaces efficiently. However, existing techniques either lead to simulator sickness due to visual and vestibular mismatch or detract users from the immersive experience that virtual reality aims to provide. This research presents innovative techniques and applications to enhance the user experience by expanding walkable, physical space in Virtual Reality. The thesis includes three main contributions. The first contribution proposes a mobile application that uses markerless Augmented Reality to allow users to explore a life-sized virtual library through a divide-and-rule approach. The second contribution presents a subtle redirected walking technique based on inattentional blindness, using dynamic foveated rendering and natural visual suppressions like blinks and saccades. Finally, the third contribution introduces a novel redirected walking solution that leverages a deep neural network, to predict saccades in real-time and eliminate the hardware requirements for eye-tracking. Overall, this thesis offers valuable contributions to human-computer interaction, investigating novel approaches to solving the locomotion dilemma. The proposed solutions were evaluated through extensive user studies, demonstrating their effectiveness and applicability in real-world scenarios like training simulations and entertainment

Inattentional Blindness for Redirected Walking Using Dynamic Foveated Rendering

Redirected walking is a Virtual Reality(VR) locomotion technique which enables users to navigate virtual environments (VEs) that are spatially larger than the available physical tracked space. In this work we present a novel technique for redirected walking in VR based on the psychological phenomenon of inattentional blindness. Based on the user's visual fixation points we divide the user's view into zones. Spatially-varying rotations are applied according to the zone's importance and are rendered using foveated rendering. Our technique is real-time and applicable to small and large physical spaces. Furthermore, the proposed technique does not require the use of stimulated saccades but rather takes advantage of naturally occurring saccades and blinks for a complete refresh of the framebuffer. We performed extensive testing and present the analysis of the results of three user studies conducted for the evaluation

SaccadeNet: Towards Real-time Saccade Prediction for Virtual Reality Infinite Walking

Modern Redirected Walking (RDW) techniques significantly outperform classical solutions. Nevertheless, they are often limited by their heavy reliance on eye-tracking hardware embedded within the VR headset to reveal redirection opportunities. We propose a novel RDW technique that leverages the temporary blindness induced due to saccades for redirection. However, unlike the state-of-the-art, our approach does not impose additional eye-tracking hardware requirements. Instead, SaccadeNet, a deep neural network, is trained on head rotation data to predict saccades in real-time during an apparent head rotation. Rigid transformations are then applied to the virtual environment for redirection during the onset duration of these saccades. However, SaccadeNet is only effective when combined with moderate cognitive workload that elicits repeated head rotations. We present three user studies. The relationship between head and gaze directions is confirmed in the first user study, followed by the training data collection in our second user study. Then, after some fine-tuning experiments, the performance of our RDW technique is evaluated in a third user study. Finally, we present the results demonstrating the efficacy of our approach. It allowed users to walk up a straight virtual distance of at least 38 meters from within a $3.5 x 3.5m^2$ of the physical tracked space. Moreover, our system unlocks saccadic redirection on widely used consumer-grade hardware without eye-tracking.Comment: redirected walking, virtual realit