We present Roomify, a spatially-grounded transformation system that generates themed virtual environments anchored to users’ physical rooms while maintaining spatial structure and functional semantics. Current VR approaches face a fundamental trade-off: full immersion sacrifices spatial awareness, while passthrough solutions break presence. Roomify addresses this through spatially-grounded transformation—treating physical spaces as “spatial containers” that preserve key functional and geometric properties of furniture while enabling radical stylistic changes. Our pipeline combines in-situ 3D scene understanding, AI-driven spatial reasoning, and style-aware generation to create personalized virtual environments grounded in physical reality. We introduce a cross-reality authoring tool enabling fine-grained user control through MR editing and VR preview workflows. Two user studies validate our approach: one with 18 VR users demonstrates a 63% improvement in presence over passthrough and 26% over fully virtual baselines while maintaining spatial awareness; another with 8 design professionals confirms the system’s creative expressiveness (scene quality: 5.95/7; creativity support: 6.08/7) and professional workflow value across diverse environments.

While Virtual Reality (VR) is increasingly employed for stress management, most applications rely heavily on audio-visual stimuli and overlook the therapeutic potential of squeezing engagement. To address this gap, we introduce VR Calm Plus, a multimodal system that integrates a pressure-sensitive plush toy into an interactive VR environment. This interface allows users to dynamically modulate the virtual atmosphere through physical squeezing actions, fostering a deeper sense of embodied relaxation. We evaluated the system with 40 participants using PANAS-X surveys, subjective questionnaires, physiological measures (heart rate, skin conductance, pulse rate variability), and semi-structured interviews. Results demonstrate that, compared to a visual-only baseline, squeeze-based interaction significantly enhances positive affect and perceived relaxation. Physiological data further revealed a state of “active relaxation”, characterized by greater reductions in heart rate and preserved autonomic flexibility (PRV), alongside sustained emotional engagement (GSR). Our findings highlight the value of coupling tangible input with immersive environments to support emotional well-being and offer design insights for future VR-based mental health tools.

Always-on sensing of AI applications on AR glasses makes traditional permission techniques inefficient for context-dependent private visual data within home environments. Home presents a challenging privacy context due to massive sensitive objects and the intimate nature of daily routines. We propose VisGuardian, a fine-grained content-based visual permission technique for AR glasses. VisGuardian features a group-based control mechanism that enables users to efficiently manage permissions for multiple private objects. VisGuardian detects objects using YOLO and adopts a pre-classified schema to group them. By selecting a single object, users can obscure groups of related objects based on criteria including privacy sensitivity, object category, or spatial proximity. A technical evaluation shows VisGuardian achieves mAP50 of 0.6704 with only 14.0 ms latency and a 1.7% increase in battery consumption per hour. Furthermore, a user study (N=24) comparing VisGuardian to slider-based and object-based baselines found it to be significantly faster for setting permissions and was preferred by users for its efficiency, effectiveness, and ease of use.

As social robots take on increasingly complex roles like game masters (GMs) in multi-party games, the expectation that physicality universally enhances user experience remains debated. This study challenges the "one-size-fits-all" view of tangible interaction by identifying a critical boundary condition: users' Negative Attitudes towards Robots (NARS). In a between-subjects experiment (N = 67), a custom-built robot GM facilitated a multi-party murder mystery game (MMG) by delivering clues either through direct tangible interaction or a digitally mediated interface. Baseline multivariate analysis (MANOVA) showed no significant main effect of delivery modality, confirming that tangibility alone does not guarantee superior engagement. However, primary analysis using multilevel linear models (MLM) revealed a reliable moderation: participants high in NARS experienced markedly lower narrative immersion under tangible delivery, whereas those with low NARS scores showed no such decrement. Qualitative findings further illuminate this divergence: tangibility provides novelty and engagement for some but imposes excessive proxemic friction for anxious users, for whom the digital interface acts as a protective social buffer. These results advance a conditional model of HRI and emphasize the necessity for adaptive systems that can tailor interaction modalities to user predispositions.

Recent HCI research has highlighted home automation’s potential in providing residents with technology-enhanced domestic autonomy. However, in the cohabitation context, the prevalent solutionist paradigm of automated systems introduces challenges to non-experts, paradoxically marginalizing specific members. This paper reports a co-creation initiative involving cohabitants, exploring a new understanding of empowerment in home automation. Participants collaborated to construct Trigger-Action Program (TAP) schemes using card-based tools during workshops. Our findings showcase how cohabitants engaged in collective ideations and embodied different negotiation patterns, which reveals the significance of more perceptible and participatory design. We frame home automation as "problematic co-design", arguing the universal overlook of collaborative resources. Furthermore, we examine how automation systems act as obstacles and sources of empowerment through the co-design lens. The paper concludes with pragmatic recommendations for designers and researchers, emphasizing the need to foster contestability for cohabitants in the evolving home automation landscape.

Understanding and recognizing emotions are important and challenging issues in the metaverse era. Understanding, identifying, and predicting fear, which is one of the fundamental human emotions, in virtual reality (VR) environments plays an essential role in immersive game development, scene development, and next-generation virtual human-computer interaction applications. In this article, we used VR horror games as a medium to analyze fear emotions by collecting multi-modal data (posture, audio, and physiological signals) from 23 players. We used an LSTM-based model to predict fear with accuracies of 65.31% and 90.47% under 6-level classification (no fear and five different levels of fear) and 2-level classification (no fear and fear), respectively. We constructed a multi-modal natural behavior dataset of immersive human fear responses (VRMN-bD) and compared it with existing relevant advanced datasets. The results show that our dataset has fewer limitations in terms of collection method, data scale and audience scope. We are unique and advanced in targeting multi-modal datasets of fear and behavior in VR stand-up interactive environments. Moreover, we discussed the implications of this work for communities and applications. The dataset and pre-trained model are available at https://github.com/KindOPSTAR/VRMN-bD.

With the development of digital technology, tourists have higher expectations for their experiences with digital cultural heritage (CH). However, there is limited research and design guidelines on how to effectively convey expert knowledge and transfer the value and connotations of digital CH to users in a virtual environment. Based on existing literature, we proposed a systematic design strategy for immersive virtual reality (IVR) systems, incorporating multimodal interaction, gamification, and storytelling for CH presentation, development, and promotion to the public. Accordingly, taking the virtual restoration of the Dunhuang murals as an example, we developed an IVR system that provided users with learning, interactive, and entertaining experiences, facilitating their transition from mere visitors to active learners while engaging with digital CH. We conducted a between-subjects user study involving 42 participants. The results demonstrated that our IVR system motivated users interests in CH, promoted CH preservation awareness, and could be applied in the domain of digital CH experiences.

Virtual Reality (VR) has the capacity to offer unparalleled immersive experiences, particularly in the domain of horror gaming. However, creating both practical and enjoyable VR applications necessitates a nuanced understanding of user emotions and behaviors. To fill this gap, we conducted semi-structured interviews with 25 participants who engaged in VR horror games, specifically exploring their emotional responses to fear-inducing stimuli and their coping strategies. The results revealed the motivations behind users' behaviors in response to different types of fear, highlighting the need to understand and manage negative emotions in VR environments, and provides insights into user needs and design methodologies in VR horror games.

Emotion recognition is a rising trend in related fields. Existing research mainly aims at the emotion recognition based on single or multi modalities on performance datasets. However, there is little research focusing on gesture-based emotion recognition using non-performance emotional datasets. In this article, we proposed a non-performance emotional data collection scheme using VR to construct a high-quality nonperformance dataset in gesture modality with fear labels. Then we proposed an optimized algorithm for gesture-based fear recognition using BLSTM on this dataset with the accuracy of up to 71.43%. Our work could be applied in many domains such as potentially domestic violence detection and VR game evaluation.

The pandemic has shifted people’s shopping behavior towards online resources. Mobile screen-based panoramic virtual reality (VR) appears to be a promising form for future online shopping. However, the existing user interface (UI) design of panoramic VR shopping needs more natural interactions based on a rational standard design guideline. In this article, we first conducted a heuristic study to compare six representative virtual store apps. This revealed a gap between users’ requirements and the current design attempts. Thus, a UI design guideline for panoramic VR in the shopping scene was presented. Then, we conducted a verification study with a demo optimized according to our design guideline. Both user experience and interactive efficiency improved as a result of the design guideline. Our design guidelines and discoveries derived from user studies provided references for the design, development, and potential use of dynamic panoramic VR in shopping scene.

In Dunhuang Mogao Grottoes, unique Buddhist murals of ancient China are preserved. Unfortunately, the exquisite murals are suffering from degradation. Experts have been trying to enhance public's awareness of mural protection, but there's no efficacious means to attract interest and popularize knowledge yet. In this paper, we propose RestoreVR, an interactive virtual reality (VR) system engaging users to experience Dunhuang mural restoration in a digital tour in the cave. Based on an online survey with the public and in-depth interviews with five Dunhuang experts, we derive a set of design requirements for generating embodied knowledge and situated experience in VR to bridge the gap between highly specialized experts and general audiences. Accordingly, we design RestoreVR and conduct a between-subjects user study to compare our system with traditional methods. The results suggest that RestoreVR significantly improves user experience and awareness of CH protection over existing methods.