GPUs can encounter memory capacity constraints, which pose challenges for achieving real-time rendering performance when processing large 3D models that exceed available memory. State-of-the-art out-of-core rendering frameworks have leveraged Level of Detail (LOD) and frame-to-frame coherence data management techniques to optimize memory usage and minimize CPU-to-GPU data transfer costs. However, the size of view-dependently selected data may still exceed GPU memory capacity, and data transfer remains the most significant bottleneck in overall performance costs. To address these, we introduce a new GPU out-of-core rendering approach that includes a LOD selection method that takes into account both memory and coherence constraints and a parallel in-place GPU memory management algorithm that efficiently assembles the data of the current frame with GPU-resident data from the previous frame and transferred data. Our approach bounds memory usage and data transfer costs, prioritizes and schedules the transfer of essential data, incrementally refining the LOD over subsequent frames to converge toward the desired visual fidelity. Our parallel memory management algorithm consolidates frame-different and reusable data, dynamically reallocating GPU memory slots for efficient in-place operations. Hierarchical LOD representations remain a core component, and we emphasize their role in supporting adaptive data transfer and coherence management, characterized by a uniform depth and near-equal patch size at all levels. Our approach adapts seamlessly to scenarios with varying levels of coherence by balancing real-time performance with visual consistency. Experimental results demonstrate that our system achieves significant performance improvements, rendering scenes with billions of triangles in real-time, outperforming existing methods while maintaining consistent visual quality during dynamic interactions.

Abstract The demand for immersive technology and realistic virtual environments has created a need for automated solutions to generate characters with morphological variations. However, existing approaches either rely on manual labour or oversimplify the problem by limiting it to static meshes or deformation transfers without shape morphing. In this paper, we propose a new cross‐parameterization approach that semi‐automates the generation of morphologically diverse characters with synthesized articulations and animations. The main contribution of this work is that our approach parameterizes deforming characters into a novel hierarchical multi‐sphere domain, while considering the attributes of mesh topology, deformation and animation. With such a multi‐sphere domain, our approach minimizes parametric distortion rates, enhances the bijectivity of parameterization and aligns deforming feature correspondences. The alignment process we propose allows users to focus only on major joint pairs, which is much simpler and more intuitive than the existing alignment solutions that involve a manual process of identifying feature points on mesh surfaces. Compared to recent works, our approach achieves high‐quality results in the applications of 3D morphing, texture transfer, character synthesis and deformation transfer.

Abstract While virtual reality (VR) games are beneficial for older adults to improve their physical functions and cognitive abilities, VR research often does not include older adults. Our review of the proceedings of major HCI conferences (i.e. ASSETS, CHI, CHI PLAY, CSCW and DIS) between 2016 and 2020 shows that only three out of 352 VR-related papers involved older adults. Consequently, older adults tend to encounter user experience (UX) problems with VR. One common way to identify UX problems is to conduct usability testing with think-aloud (TA) protocols. As VR games tend to be perceptually and physically demanding, older adults might need to allocate more resources to VR content and interaction and thus have fewer resources for thinking aloud. This raises the question of whether TA protocols are still a viable approach to detecting UX problems of VR games for older adult participants. To answer this question, we conducted usability testing with older adults who played two common types of VR games (i.e. the exergame and experience game) using concurrent and retrospective TA protocols (i.e. CTA and RTA), which are widely used in the industry. We analyzed participants’ TA verbalizations and uncovered how different categories of verbalizations indicate UX problems. We further show how older adults perceived the effects of thinking aloud on their game experiences in two TA protocols and offer design implications.

This work presents the design and evaluation of three bimanual interaction modalities for cross-workspace interaction in virtual reality (VR), in which the user can move items between a personal workspace and a shared workspace. We conducted an empirical study to understand three modalities and their suitability for cross-workspace interaction in VR.

In a situation where a large and chaotic collection of digital images must be manually sorted or categorized, there are two challenges: (1) unnatural actions during a prolonged human-computer interaction and (2) limited display space for image browsing. An immersive 3D interface is prototyped, where a person sorts a large collection of digital images with his or her bare hands in a virtual environment, and performs hand motions matching characteristics of sorting gestures in the real world. The virtual reality environment provides extra levels of immersion for displaying images.