As virtual reality (VR) technology becomes cheaper, higher-quality, and more widely available, it is seeing increasing use in a variety of applications including cultural heritage, real estate, and architecture. A common goal for all these applications is a compelling virtual recreation of a real place. Despite this, there has been very little research into how users perceive and experience such replicated spaces. This article reports the results from a series of three user studies investigating this topic. Results include that the scale of the room and large objects in it are most important for users to perceive the room as real and that non-physical behaviors such as objects floating in air are readily noticeable and have a negative effect even when the errors are small in scale.

Visualizing History: Tunnels of Vauquois is an educational immersive virtual reality exhibit that makes the invisible history of World War I soldiers' experiences in the tunnels of Vauquois, France visible to contemporary audiences. Using a head-mounted display, a virtual environment recreated from scanned data of the original site, redirected walking, passive haptics, aligned physical and virtual environments, interactive tracked props, and narration, the exhibit presents the visitor with both discrete knowledge and the opportunity for emotional awareness. In this paper, we describe the motivation and rationale for creating an immersive exhibit for informal learning environments such as museums, libraries, and school virtual reality labs. We also describe how the current exhibit functions and our iterative design process informed by observational feedback from pilot testing.

Digitals twins, used to represent dynamic environments, require accurate tracking of human movement to enhance their real-world application. This paper contributes to the field by systematically evaluating and comparing pre-existing tracking methods to identify strengths, weaknesses and practical applications within digital twin frameworks. The purpose of this study is to assess the efficacy of existing human movement tracking techniques for digital twins in real world environments, with the goal of improving spatial analysis and interaction within these virtual modes. We compare three approaches using indoor-mounted lidar sensors: (1) a frame-by-frame method deep learning model with convolutional neural networks (CNNs), (2) custom algorithms developed using OpenCV, and (3) the off-the-shelf lidar perception software package Percept version 1.6.3. Of these, the deep learning method performed best (F1 = 0.88), followed by Percept (F1 = 0.61), and finally the custom algorithms using OpenCV (F1 = 0.58). Each method had particular strengths and weaknesses, with OpenCV-based approaches that use frame comparison vulnerable to signal instability that is manifested as “flickering” in the dataset. Subsequent analysis of the spatial distribution of error revealed that both the custom algorithms and Percept took longer to acquire an identification, resulting in increased error near doorways. Percept software excelled in scenarios involving stationary individuals. These findings highlight the importance of selecting appropriate tracking methods for specific use. Future work will focus on model optimization, alternative data logging techniques, and innovative approaches to mitigate computational challenges, paving the way for more sophisticated and accessible spatial analysis tools. Integrating complementary sensor types and strategies, such as radar, audio levels, indoor positioning systems (IPSs), and wi-fi data, could further improve detection accuracy and validation while maintaining privacy.

A multi-platform Virtual Reality (VR) approach is proposed to complement the traditional approaches for construction safety training. Visual simulations of a highway construction project were developed and presented through the developed platforms, aiming at giving students immersive experience of actual construction environments. The simulated worksite scenarios included active traffic, multiple worker roles and heavy equipment, and was rendered at different times of day and weather conditions. We used this material in an undergraduate class activity with 50 students. During a session in our visualization lab, students experienced the scenarios presenting day shift, afternoon shift with adverse weather and night shift and were asked to develop daily report of their job site observation. The scenrios were presented via the following platforms: TV projection, Mobile Phone, Head-Mounted Display (HMD), and CAVE projection room. The results demonstrates that the multi-platform immersive experience has the potential to significantly improve hazard recognition skill of construction students.