Translation gain is a key Redirected Walking (RDW) technique in Virtual Reality (VR) that enables users to navigate virtual environments (VEs) larger than the available physical space. The technique was originally developed to scale users' walking distance in the VE and is typically applied continuously, regardless of the user's motion state. We introduce Gait-Synced Translation Gain (GSTG), a novel approach that adapts translation gain by synchronizing it with the user's gait cycle. GSTG leverages the single-limb support phase of walking-when users are less stable and thus less sensitive to external disturbances-to apply higher levels of gain. This approach allows greater manipulation while preserving natural walking sensations and avoiding additional cybersickness. A user study comparing GSTG with continuous translation gain demonstrates significant improvements in perceived naturalness and comfort. Our results highlight the potential of gait-synchronized gain to enhance immersion, offering new possibilities for more realistic and comfortable VR locomotion.

Objective:To evaluate the clinical efficacy of an adaptive vestibular rehabilitation training system based on Virtual Reality (VR) technology for patients with semicircular canal injury. Methods:A randomized controlled trial was conducted with 60 patients diagnosed with peripheral vestibular vertigo. Participants were randomly assigned to either an Intervention Group (n=30), which received VR-based adaptive vestibular rehabilitation using the PICO 4 Pro system, or a Control Group (n=30), which underwent traditional vestibular rehabilitation. Both groups received training for four weeks. The primary outcome measure was the Dizziness Handicap Inventory (DHI). Secondary outcomes included balance performance assessed via the Activities-specific Balance Confidence (ABC) Scale and static posturography (Maximum Sway Path Length and Sway Area). Vestibular function was objectively evaluated using the Video Head Impulse Test (vHIT) and the Bithermal Caloric Test. Psychological status was assessed using the Hospital Anxiety and Depression Scale (HADS). Results:Post-intervention analysis revealed that the Intervention Group achieved significantly lower DHI scores compared to the Control Group. In terms of balance, the Intervention Group demonstrated significantly higher ABC Scale scores and reduced Maximum Sway Path Length and Sway Area compared to controls. Furthermore, the Intervention Group showed a significantly lower rate of abnormal findings in both vHIT and Bithermal Caloric Tests, indicating improved physiological function. Improvements in psychological well-being were also observed, with the Intervention Group exhibiting significantly lower HADS scores. Conclusion:VR-based adaptive vestibular rehabilitation is effective in alleviating vertigo symptoms, enhancing balance function, and improving psychological well-being. The intervention also promotes the physiological recovery of semicircular canal function, demonstrating superior clinical efficacy compared to traditional rehabilitation methods.

Age significantly influences human motor patterns, yet existing virtual reality (VR) systems lack dynamic modelling of these variations. This paper introduces AgeStyle, a versatile framework that integrates age-guided style selection with motion style transfer to convert user-uploaded videos into interactive 3D motion models. Utilizing 2D joint detection and 3D pose estimation, AgeStyle constructs motion representations enhanced by a CLIP-driven Cross-Attention module, capturing the distinct traits of different age groups—child flexibility, adult efficiency, and elderly stability. Our system enables real-time switching between motion styles and perspectives through voice commands, offering an immersive exploration of age-related movements. Quantitative experiments on the XIA dataset demonstrate AgeStyle’s competitive performance in both content preservation and style consistency, achieving average CC and SC++ scores of 7.4 and 14.8, respectively. AgeStyle represents a meaningful advancement in VR character design, with broad potential applications in education, healthcare, rehabilitation, and interactive entertainment. For the demo, please refer to https://youtu.be/eo7Shy0Ukps. The source code of AgeStyle is available at https://github.com/codeozzz/ageStyle.

In immersive virtual reality (VR) environments, users often face safety risks due to limited spatial awareness, such as unintentionally approaching or crossing physical boundaries. To address this challenge, we propose a novel boundary warning risk assessment system to enhance spatial perception and operational safety. Our system continuously computes a risk score based on four key kinematic features: the user’s distance to the boundary, velocity, acceleration, and the angle between movement direction and boundary orientation. Based on this score, we designed and compared four feedback strategies: a progress bar indicating risk level, a color-coded circular indicator with gradient transitions, auditory cues with varying frequencies, and a combined multimodal approach integrating visual and auditory feedback. A user study (n = 24) was conducted where participants navigated a 4 × 4 m virtual space with the objective of collecting as many targets as possible. We measured both objective safety metrics and subjective user experience ratings to assess the user perception of our proposed methods. Results showed that different feedback strategies led to noticeable differences in safety performance. Of the four methods tested, the Multimedia Cue was the most effective, significantly reducing boundary intrusions and receiving the highest user preference ratings.

This paper introduces a novel VR-based system that redefines the acquisition of Hanzi character literacy by integrating traditional mortise-tenon joinery principles (HVRMT). Addressing the challenge of abstract character memorization in digital learning, our system deconstructs Hanzi components into interactive “structural radicals” akin to wooden joint modules. Leveraging PICO’s 6DoF spatial tracking and LLM’s morphological analysis, learners assemble stroke sequences with haptic feedback simulating wood-to-wood friction. Our system also supports multiplayer online experiences, enhancing engagement and memory retention while preserving intangible cultural heritage. This innovative approach not only enhances engagement and memory retention but also reconstructs the craft wisdom embedded in Chinese writing systems, offering new pathways for preserving intangible cultural heritage in digital ecosystems. For the demo, please refer to this link .

Sketching education, a cornerstone of visual arts, often leads to a disconnect between abstract theory and practical application when teaching spatial relationships and dynamic light or shadow principles. This study presents an XR headset application built on a novel three-layer teaching framework: basic modeling, cognitive deepening, and creative expression. Leveraging XR’s immersive capabilities, the system integrates real-time sketch conversion, dynamic light source simulation, and spatial walking interaction. Small-scale user experiments confirm this paradigm, which merges real-object observation with XR enhancement, significantly improves learning outcomes, particularly in enhancing structural understanding and achieving a 75

Redirected walking (RDW) is a virtual reality locomotion technique that enables users to explore large virtual environments within a limited physical space. While state-of-the-art methods based on physical trajectory planning make effective use of physical space, some of them often compromise user comfort due to frequent directional reversals in curvature gain. To address this, this paper proposes a novel RDW method that integrates strafing gain with pose score guidance. Our approach discretizes the physical space into a series of standard poses, each with a long-term safety score, and redirects the user toward the optimal pose. The main contribution is a path generation algorithm that decomposes redirection into two sequential stages to ensure stable gains for each planned path: it first uses the curvature gain to steer the user along an arc for orientation alignment, and then inserts a straight path segment with constant strafing gain to achieve positional alignment with the target pose. Simulation experiments demonstrate a reduction in resets, while the user study shows lower Simulator Sickness Questionnaire scores compared to previous methods. Our work explores the potential of combining novel gains with state-of-the-art methods to create a more effective and comfortable RDW controller algorithm.

We present a novel 360° panoramic video conferencing system that dynamically synchronizes virtual backgrounds with real-time camera motion, addressing the limitations of static backgrounds in conventional systems. By integrating robust human segmentation, monocular visual odometry (VO), and virtual environment rendering, our method achieves seamless alignment between foreground participants and immersive 3D virtual scenes. Unlike prior approaches that suffer from foreground-background desynchronization during camera rotations or user movements, our framework estimates camera rotation in 3-DoF using a hybrid pipeline combining feature-based patch tracking and pose smoothing, while ignoring translation artifacts to maintain stability. This work bridges the gap between computational efficiency and MR-driven telepresence, offering a practical solution for next-generation virtual collaboration.

Redirected Walking (RDW) in virtual reality relies on carefully calibrated translation gain to maintain a natural mapping between physical and virtual spaces. However, most existing gain strategies assume the user maintains a horizontal viewing direction, ignoring the potential effects of head pitch angle. This oversight can lead to perceptual bias and reduce redirection quality. In this paper, we investigate how the user’s Point of Subjective Equality (PSE) and perceived threshold ( σ ) for virtual speed changes vary with head pitch. Using a psychophysical approach, we guided users through a speed discrimination task and collected speed perception judgments and subjective discomfort scores across seven pitch angles. Results showed that users tended to underestimate speed when looking upward (with significantly higher PSE), while speed was overestimated and σ decreased in downward conditions, indicating increased speed sensitivity. This trend held across scenes, though exact values varied. SSQ assessments further showed that upward views were more likely to induce motion sickness, whereas horizontal and mildly upward views were more comfortable. These findings reveal the impact of head pitch on speed perception and user experience, providing an empirical basis for adaptive gain control in VR.

The rise of Virtual Reality (VR) sports has been driven by evolving work patterns, limited access to physical exercise spaces, and a growing focus on health and wellness. Beyond the enjoyment and convenience offered by VR exercise, we aim to enhance users' athletic performance through this medium. Prior research on the Proteus Effect in VR sports has demonstrated the potential of customized, stronger, or younger avatars to improve exercise outcomes. However, such effects are limited for users who already perceive themselves as strong and youthful. To address this, we propose a more general approach: representing perceived avatar capability through facial expressions and vocal cues to influence user performance. In this study, we examined how manipulating the perceived capability level of virtual avatars (high, neutral, low) during dumbbell lateral raises in a VR gym affected exercise performance. Results indicated that avatars with high-capability expressions significantly enhanced performance and motivation compared to low-capability avatars. These findings underscore the promise of using facial and auditory cues to represent perceived capability, offering new directions for designing emotionally intelligent fitness applications.

Redirected walking (RDW) utilizes gain adjustments within perceptual thresholds to allow natural navigation in large-scale virtual environments (VEs) within confined physical environments (PEs). Previous research has found that when users are distracted by some scene elements, they are less sensitive to gain values. However, the effects on detection thresholds have not been quantitatively measured. In this paper, we present a novel method that dynamically adjusts translation gain by leveraging visual distractors. We place distractors within the user’s field of view and apply a larger translation gain when their attention is drawn to them. Because the magnitude of gain adjustment depends on the user’s level of engagement with the distractors, the redirection process remains smooth and unobtrusive. To evaluate our method, we developed a task-oriented virtual environment for a user study (n = 26). Results show that introducing distractors in the virtual environment significantly raises users’ translation gain thresholds. Furthermore, assessments using the Simulator Sickness Questionnaire (SSQ) and Igroup Presence Questionnaire (IPQ) indicate that the method maintains user comfort and acceptance, supporting its effectiveness for RDW systems.

Cave Automatic Virtual Environments (CAVEs) remain an important class of projection-based, room-scale virtual reality (VR) systems, offering co-located, face-to-face immersion for a versatile range of fields that head-mounted displays cannot match. Although existing reviews typically emphasize hardware configurations, display technologies, and application areas, collaboration, a defining advantage of co-located and networked projection-based virtual reality, has received comparatively limited and fragmented attention. This survey addresses this gap through a broad, structured review of over 100 publications (1992-2025) spanning early prototypes to contemporary domain-specific installations. We analyze CAVE research from four perspectives: application domains, interaction methods, system configurations, and collaboration support. In contrast to earlier work, we treat collaboration not as a supporting feature but as a critical design variable. Across domains, multi-user support is inconsistently realized, commonly reported in the reviewed literature for education and visualization, but less integrated in cultural and medical applications. Where present, collaborative features often reported to prioritize co-presence over shaping system architecture or interaction design. By foregrounding collaboration alongside interaction, domain context, and system design, this survey documents patterns, highlights observed mismatches between domain needs and system advantages, and outlines opportunities for more intentional collaboration support of shared immersive experiences.

As technology advances, user demand for immersive and authentic information presentation rises. Traditional 2D displays and interactions fail to meet modern standards, while virtual reality (VR) is gaining attention for its immersive experience. However, using a controller for VR movement can cause dizziness due to mismatched visual and vestibular cues, impacting the VR experience. This paper analyzes the main causes of VR-induced vertigo and develops improved handheld controller movement strategies. These strategies adjust the user’s pitch angle and field of view in real time or map the user’s real-world head acceleration to the virtual character. By intelligently adjusting the controller-to-VR display mapping, these methods reduce vertigo. In addition, this paper also verified the actual effects of these designs through a series of experiments, and conducted detailed data analysis on the degree of user vertigo. The experimental results showed that using a specific improved handheld controller movement design can significantly improve the user’s comfort in the VR environment, effectively reducing the occurrence of vertigo and discomfort.

In social virtual reality (VR), maintaining appropriate interpersonal distance is essential for user comfort and privacy. However, most existing locomotion methods provide limited support for respecting personal space, leaving users vulnerable to unintentional or socially inappropriate intrusions. To address this issue, we propose potential field-guided teleportation, a proactive locomotion framework consisting of two method implementations that dynamically adjust teleportation targets based on real-time interpersonal proximity, preventing entry into others' personal spaces without explicit user intervention. We evaluate our technique through two user studies: a preliminary study exploring energy-based constraint parameters, followed by a comparative study against conventional and negotiated teleportation methods. Experiments were conducted in socially interactive VR scenarios populated with simulated users exhibiting human-like behaviors. Results demonstrate that our methods reduce perceived social anxiety while maintaining locomotion efficiency and usability. This work presents a socially-aware locomotion strategy that balances personal space protection with effective and socially appropriate movement in shared virtual environments.

Redirected Walking (RDW) is a locomotion technique utilized in virtual reality. It involves manipulating the displayed scene to redirect the user without their awareness, causing them to adjust their position and orientation naturally in response to perceived motion. This technique enhances the user's immersion and smoothens their exploration of the virtual environment, enabling them to navigate a greater range of virtual spaces within a confined physical area. One key element in redirected walking is translation gain, which scales the speed of the user's virtual movement, allowing them to traverse the virtual environment faster or slower. However, its effectiveness is constrained by the detection threshold imposed on it. Since translation gain primarily capitalizes on the imprecision of human distance perception, while in real life telescopes can also confuse people's judgment of distance, taking inspiration from this phenomenon, we propose an approach called Walking Telescope. The Walking Telescope approach involves modifying the field of view (FoV) by filling the entire headset view with a small range of viewpoints. We discovered that the threshold range of translation gain expands when the FoV is smaller than the original FoV of the headset. Furthermore, as the FoV gradually decreases, the threshold range of translation gain progressively expands. As a comparison, we also experimented with reducing the FoV by simply decreasing the visual range. This method does not produce a zoom-in effect similar to that of a telescope. To ensure user comfort, we identified a suitable FoV range by calculating the Simulator Sickness Questionnaire (SSQ) score. This approach allows for an expanded threshold range for translation gain without reducing the user's comfort level.

With the recent rise of Metaverse, online multiplayer VR applications are becoming increasingly prevalent worldwide. However, as multiple users are located in different physical environments, different reset frequencies and timings can lead to serious fairness issues for online collaborative/competitive VR applications. For the fairness of online VR apps/games, an ideal online RDW strategy must make the locomotion opportunities of different users equal, regardless of different physical environment layouts. The existing RDW methods lack the scheme to coordinate multiple users in different PEs, and thus have the issue of triggering too many resets for all the users under the locomotion fairness constraint. We propose a novel multi-user RDW method that is able to significantly reduce the overall reset number and give users a better immersive experience by providing a fair exploration. Our key idea is to first find out the "bottleneck" user that may cause all users to be reset and estimate the time to reset given the users' next targets, and then redirect all the users to favorable poses during that maximized bottleneck time to ensure the subsequent resets can be postponed as much as possible. More particularly, we develop methods to estimate the time of possibly encountering obstacles and the reachable area for a specific pose to enable the prediction of the next reset caused by any user. Our experiments and user study found that our method outperforms existing RDW methods in online VR applications.

Redirected Walking (RDW) is an important intermediary layer in virtual reality (VR) interaction systems. It addresses the issues of spatial restrictions in VR exploration by imperceptibly remapping the virtual environment’s movement to the physical environment, enhancing the user’s immersive experience. In VR, jumping is also a noteworthy motion besides walking. However, existing redirected walking (RDW) algorithms typically focus on reducing collisions between users and obstacles during walking but overlook the safety when users perform significant actions such as jumping. This oversight can pose serious risks to users during VR exploration, especially when there are physical obstacles or boundaries near the virtual locations that require user jumping. We propose SafeRDW, the first RDW algorithm that takes the user’s jumping safety into consideration. The proposed method considers both walking and jumping actions in the virtual environment, reducing physical resets and redirecting users to safer locations when a jump is required in the virtual space, ensuring user safety. Simulation experiments and user study results both show that our method not only reduces the number of resets, but also significantly ensures user safety when they reach the jumping points in the virtual scene.

Rotation gain is a subtle manipulation technique commonly employed in Redirected Walking (RDW) methods due to its superior capability to alter a user’s virtual trajectory. Previous studies have reported that the imperceptible ranges of rotation gains are influenced by various factors, resulting in different detection threshold values, which may alter RDW performance. In this study, we focus on the effects of scene visual characteristics on the rotation gain and rotation gain thresholds (RGTs), which have been less explored in this area. In our experiments, we focus on three visual characteristics: visual density, spatial size, and realism. Each characteristic is tested at two different levels, resulting in a design of eight distinct VR scenes. Through extensive statistical analysis, we find that spatial size may influence user perception of rotation gain in different virtual environments (VEs), though the effect appears to be small. No significant results of sensitivity differences were found for visual density and realism. We show that the short-term temporal effect is another predominant factor influencing user perception of rotation gain, even when users experience different visual stimuli in VEs, such as different scene visual characteristic settings in our study. This result indicates that users’ adaptation effects on rotation gain can occur in as short a time as overnight intervals, rather than over weeks.