Target selection-based teleportation is one of the most prevalent locomotion techniques in immersive virtual environments, mitigating visual motion sickness and overcoming physical space constraints. However, the conventional Point & Teleport method, widely implemented in commercial VR systems, restricts navigation to planar surfaces, limiting exploration of mid-air positions essential for tasks such as obtaining elevated viewpoints or bypassing obstacles. Mid-air teleportation extends the Point & Teleport metaphor to support free navigation in three-dimensional space, yet the influence of visual feedback on its performance and usability remains underexplored. This paper investigates six different implementations of visual feedback techniques during target specification in mid-air teleportation. We evaluated these techniques through a user study with 56 participants. The results reveal trade-offs between the downward-facing camera, which achieves the highest accuracy, and other visual feedback techniques that rely on occlusion cues, such as the spherical pointer, the spherical boundary, the ground reference cylinder, and the avatar, which result in lower task completion time. We propose initial design guidelines for target selection-based mid-air teleportation based on our findings.

Cross Reality (CR) is a new emerging field based on the current developments in Mixed Reality hardware, especially supported by the broad market penetration of video-based see-through Head-Mounted Displays. It refers to applications that span across different stages (real, Augmented Reality, Augmented Virtuality, Virtual Reality) of the reality-virtuality continuum, where users are interconnected between different stages and/or are able to transition between these stages. This publication follows the concept of other grand challenges publications and reflects the discussion of various researchers invested in CR. After an initial discussion at the 1stJoint Workshop on Cross Reality at IEEE ISMAR 2023, six topic groups have been identified, leading to 22 challenges, which were discussed in groups over the period of multiple months. The discussion of these challenges should act as a road map for future research in the area of CR.

To support speech-based object selection in eXtended reality (XR) environments, we evaluated four natural language processing (NLP) pipelines that vary in their use of large language models (LLMs). While LLM-based pipelines achieve higher accuracy in selecting annotated scene objects, they suffer from increased response latency. In contrast, traditional rule-based NLP tools offer faster responses but lower accuracy. To balance these trade-offs, we designed a hybrid pipeline that selectively routes utterances to an LLM only when complexity warrants it. Results show it maintains low latency for simple commands in our test corpus while improving accuracy for more complex commands.

The paper summarizes the contributions to the AVI 2024 workshop on Prototyping and Developing Real-World Applications of Extended Reality.

The paper investigates how users want to transfer 3D virtual objects between a standard desktop monitor and an augmented reality head-mounted display setup during a Cross Reality session. An elicitation study with 20 participants was conducted to gather their preferred interactions and input modalities to select 3D virtual objects and trigger the transition. Participants were allowed to propose interactions belonging to various input modalities or a combination of interactions that utilize multiple input modalities. We labeled the observed data and analyzed the resulting 1200 input observations to derive a set of recommended interactions. We found that mid-air hand gestures Drag, Tap, and Grab were the most commonly proposed interactions and should be considered as the primary interaction for CR virtual objects transition assisted with other interactions and input modalities as the supplementary base on different user scenarios.

By leveraging the strengths of virtual reality (VR) technologies, we have created a prototype reservoir model analysis VR tool aimed to advance reservoir analysis workflows beyond conventional methods by improving how one understands, analyzes, and interacts with reservoir model visualizations. We present and discuss the results of a usability study conducted with reservoir engineering experts to evaluate this tool and help determine in what ways virtual reality may offer an improved experience over conventional approaches when performing three common reservoir model analysis tasks: the spatial filtering of model cells using movable planes, the cross-comparison of multiple models, and well path planning. The study found that accomplishing these tasks with our VR tool was generally regarded as easier, quicker, more effective, and more intuitive than traditional model analysis software while maintaining a feeling of low task workload on average. Overall, participants provided positive feedback regarding their experience with using VR to perform reservoir engineering work tasks and found VR improved multi-model cross-analysis and rough object manipulation in 3D, indicating the potential for VR to be better than conventional means for some work tasks. They also expressed they could see it best utilized as an addition to current software to assist reservoir model analysis workflows, however, there were some concerns voiced that would be best addressed before VR was fully adopted into their work.

Cross-reality (CR) applications allow users to utilize tools for problem solving that reside on different points of the Milgram reality-virtuality spectrum. Design guidelines for such applications are missing. In this paper, we are proposing a design space focusing on single-user Cross Reality applications as a tool for guiding research and development projects.