High Dynamic Range (HDR) panoramic video is crucial to enhance immersive experience in Virtual Reality (VR). However, a hurdle is that panoramic cameras often struggle with limited dynamic range and motion blur. Inspired by the event-driven sensing of the human eye, this paper explores the potential of the event cameras to enhance panoramic HDR video reconstruction. As a pioneering research endeavor, we first starts by designing a novel hybrid imaging platform equipped with preprocessing pipelines for event-panorama synchronization, alignment, and HDR ground truth generation. Based on the platform, we then introduce Ev-Pano, the first event-panorama HDR video covering diverse indoor scenes for panoramic HDR video reconstruction. We hope Ev-Pano will establish a foundation to support event-guided panoramic HDR imaging and VR research community. With Ev-Pano, we further propose a novel approach that employs a weighting function-based luminance fusion to enable events to recover missing textures in LDR panoramic videos for panoramic HDR video reconstruction. We conduct extensive experiments to demonstrate the effectiveness of our approach. The results show the best performance of ours than prior arts. Meanwhile, a user study on an HDR-capable head-mounted display (Apple Vision Pro) shows feasible perceptual quality (which is closer to the HDR ground truth) of the reconstructed panoramic HDR videos. The codes and part of the dataset can be accessed via the anonymized link https://anonymous.4open.science/r/Ev-Pano-D2D2/.

Users are more likely to experience visually induced motion sickness (VIMS) during passive motion in virtual reality (VR), particularly in passive virtual driving scenarios. To solve this challenge, we propose a Multi-sensory Simulation of Wind Sensation (MSSWS) method to alleviate VIMS symptoms by enhancing the user’s sense of embodiment (SoE). The method utilizes low-fidelity airflow simulation to align vestibular perception with visual, auditory, and tactile cues. Then, we developed an interactive wind simulation helmet that can generate low-fidelity airflow along four directional axes around the user’s head, and implemented a passive virtual motorcycle riding environment with synchronized visual and auditory feedback matching the airflow patterns. A user experiment was conducted to systematically evaluate the effectiveness of MSSWS in enhancing SoE and reducing VIMS under various conditions, including helmet activation states, speed variations, and movement directions, with additional validation conducted in a Cave Automatic Virtual Environment (CAVE). Experimental results show that MSSWS significantly enhances sense of presence and SoE while substantially reducing VIMS during passive navigation. Notably, MSSWS shows significantly greater effects on VIMS in high-risk conditions characterized by rapid speed changes and multi-directional movement.

Integrating artificial intelligence (AI) with immersive analytics (IA) represents a promising means of leveraging advanced computational techniques to enhance data visualization and analysis. This study examines the state-of-the-art of AI-IA integration by addressing three key research issues: the significant application domains, the AI techniques used and their combinations, and current challenges and future directions. Results of reviewing 43 relevant studies reveal that AI-IA integration is still in its early stages, as existing research has mainly focused on a limited range of data types and application scenarios. By analyzing the application domains, this systematic literature review supports previous findings of important applications in the fields of education, manufacturing, and healthcare. At the same time, it identifies emerging applications that have progressed from XR and AI domains to AI-IA integration, such as sports events, assistive systems, urban planning, and disaster management. We contribute to extending established visual analytics (VA) pipelines into XR environments with integrated AI techniques. AI techniques are identified as contributing in five ways to this IA pipeline. Our contribution also includes identifying four key challenges and seven opportunities for future exploration. The review concludes that combining AI and IA holds the potential to create innovative applications using advanced AI and immersive visualization techniques. We present an overview of these applications and address key issues for future development.

Virtual reality (VR), particularly through multi-user VR systems, enhances collaboration and immersion. However, multi-team VR systems (MTVR), which allow several teams to interact, either by cooperating or competing, are less studied. Drawing inspiration from concepts in game theory, specifically the positive-sum game (PSG) and zero-sum game (ZSG), this study investigated the impact of inter-team competition modes at the team level and haptic feedback at the individual level on team flow and individual flow for the first time. An experimental MTVR that supports inter-team competition in a two-person vs two-person pattern was implemented first. Then, a$2 \times 2$within-subject experiment was conducted to examine the effects of different inter-team competition modes (PSG/ZSG) and haptic feedback (on/off). The results based on 188 participants indicate that the PSG mode leads to significantly higher levels of collective ambition and improved team relationships compared to the ZSG mode. Furthermore, providing haptic feedback can significantly enhance awareness of shared and personal task goals, resulting in more cautious performance during teamwork.

This work investigates how prior VR experience influences interactions in a multi-user metaverse-based cultural heritage game. Results show that prior VR experience enhanced usability and control in the VR condition, while participants without prior experience reported greater enjoyment and novelty. Statistical analysis revealed a significant difference in perspicuity between experience levels in the VR condition and in stimulation in the non-VR condition.

In this paper, we propose p-Blend, an efficient and effective blendshape perturbation mechanism designed to defend against both intra- and cross-app re-identification attacks in virtual reality. p-Blend provides privacy protection when streaming blendshape data to third-party applications on VR devices. In its design, we consider both privacy and utility. p-Blend not only perturbs blendshape values to resist re-identification attacks but also preserves the smoothness of facial animations and the naturalness of facial expressions, ensuring the continued usability of the data. We validate the effectiveness of p-Blend through extensive empirical evaluations and user studies. Quantitative experiments on a large-scale dataset collected from 45 participants demonstrate that p-Blend significantly reduces re-identification accuracy across a range of machine learning models. While pure-random perturbation fails to prevent attacks that exploit statistical features, p-Blend effectively mitigates these risks in both raw and statistical blendshape data. Additionally, user study results show that facial animations generated from p-Blend-perturbed blendshapes maintain greater smoothness and naturalness compared to those using purely random perturbation. The codes and dataset are available at https://github.com/jingwei1016/p-Blend.

Abstract In this paper, we investigate the current state and development of personalized smart immersive extended reality environments (PSI-XR). PSI-XR has gained increasing traction across various fields such as education, entertainment, and healthcare, offering customized immersive experiences that address users’ personalized needs. This study performs a systematic literature review by collecting and analyzing related journal and conference papers in the domain. Following a comprehensive search across three databases, which yielded 1276 papers, a refined selection of 94 publications was made to conduct an in-depth analysis of cutting-edge research in the field of PSI-XR. This review focused on examining application domains, relevant technologies, and smart techniques, including artificial intelligence, with particular emphasis on advancements in personalization. The study provides insights into prospective advancements while also identifying the opportunities and challenges in this evolving field. This review is beneficial for both researchers and developers interested in exploring the state-of-the-art personalized perspective in a smart immersive extended reality environment.

Virtual reality, augmented reality, and mixed reality (VR/AR/MR) as information and communication technologies have been recognised and implemented in healthcare in recent years. One of the popular application ways is games, due to the potential benefits of providing an engaging and immersive experience in a virtual environment. This study presents a systematic literature review that evaluates the state-of-the-art on VR/AR/MR game applications in healthcare by collecting and analysing related journal and conference papers published from 2014 through to the first half of 2020. After retrieving more than 3,000 papers from six databases, 88 articles, from both computer science and medicine, were selected and analysed in the review. The articles are classified and summarised based on their (1) publication information, (2) design, implementation, and evaluation, and (3) application. The presented review is beneficial for both researchers and developers interested in exploring current research and future trends in VR/AR/MR in healthcare.