AR-Based Spatial Figure Learning with Tangible Vertex Markers on a Wireframe Cube

PurposeIn recent years, there has been significant interest in adopting XR (extended reality) technologies such as VR (virtual reality) and AR (augmented reality), particularly in retail. However, extending activities through reality-mediation is still mostly believed to offer an inferior experience due to their shortcomings in usability, wearability, graphical fidelity, etc. This study aims to address the research gap by experimentally examining the acceptance of metaverse shopping.Design/methodology/approachThis study conducts a 2 (VR: with vs. without) × 2 (AR: with vs. without) between-subjects laboratory experiment involving 157 participants in simulated daily shopping environments. This study builds a physical brick-and-mortar store at the campus and stocked it with approximately 600 products with accompanying product information and pricing. The XR devices and a 3D laser scanner were used in constructing the three XR shopping conditions.FindingsResults indicate that XR can offer an experience comparable to, or even surpassing, traditional shopping in terms of its instrumental and hedonic aspects, regardless of a slightly reduced perception of usability. AR negatively affected perceived ease of use, while VR significantly increased perceived enjoyment. It is surprising that the lower perceived ease of use appeared to be disconnected from the attitude toward metaverse shopping.Originality/valueThis study provides important experimental evidence on the acceptance of XR shopping, and the finding that low perceived ease of use may not always be detrimental adds to the theory of technology adoption as a whole. Additionally, it provides an important reference point for future randomized controlled studies exploring the effects of technology on adoption.

Introduction Novel medical technologies are necessary to support virtual health in low bandwidth environments. When tele-mentoring is not possible, advanced clinical decision support tools can deliver essential medical knowledge to assist novice clinicians. These tools can fill knowledge gaps in specialty fields, like burn. We developed the Augmented Reality Burn Assist Manager (ARBAM), a novel, comprehensive augmented reality (AR)-based burn management platform to address key tasks in burn care. Methods A randomized 2x2 cross-over design was used to investigate if ARBAM could enhance a user’s ability to care for a simulated burn patient as compared to standard clinical practice guidelines (CPGs). We developed the software for use on a mixed reality, head-mounted device. Participants were clinicians with little to no burn care experience, and were asked to complete 4 key tasks, twice each, using either paper copies of the Joint Trauma System’s CPGs and supplemental worksheets first (Paper) or our AR technology. Tasks included calculating burn size (TBSA), performing medication dosage calculations (MC), managing a burn fluid resuscitation (FR), and performing a simulated escharotomy (EC). All tasks were evaluated for completion time and accuracy. Cross-over analysis of treatment effects used a two-sided, two-sample t-test or Wilcoxon Rank-Sum test as appropriate. Results Eleven participants were randomized: 5 started with Paper and 6 started with AR. Time to perform FR was statistically different (p< 0.05) with AR taking less time than Paper (4.8 vs. 7.0 mins, respectively). FR clinical performance was also better in the AR group with a mean accuracy score of 99% vs. 52% for Paper (p< 0.001). EC completion times were not clinically or statistically different. However, EC accuracy was 93% for AR compared to 55% for Paper (p< 0.001). Although not statistically different, MC performance accuracy was considerably better for AR (91%) than for Paper (66%). No differences between groups were observed for TBSA or MC completion times nor TBSA accuracy. Conclusions Compared to traditional tools, AR may enhance a clinician's ability to complete key tasks in the initial management of a burn patient. This technology may be helpful during disasters when tele-mentoring is not available. Limitations of this study include a small sample size, limited user training on the AR device, and potential carry-over effects. Therefore, generalizations cannot be made about wide-scale usage. Nonetheless, this study showed that AR may be helpful in managing lifesaving burn tasks. Applicability of Research to Practice ARBAM may enhance decision making by novice clinicians when caring for burn patients. Our data demonstrate the potential for AR-based support tools to improve burn care delivery and reduce error rates for novice clinicians, which could lead to reductions in morbidity and mortality. Future research is needed to investigate how AR technology can be used for other lifesaving interventions.

Augmented Reality (AR) is one of the latest developments in human-computer interaction technology. It aims to generate illusions from seamless fusion of virtual objects and real world. Typical AR system requires two basic parts: three-dimensional registration and real-virtual fusion. Occlusion handling is crucial for visual realism. To optimize visual realism, we generated a real-time systematic architecture to operate occlusion handling. The architecture is based on RGBD images, and it consists of three parts: real-time camera tracking system, 3D reconstruction system and AR fusion system. Specifically, we used a two-pass scheme strategy to execute the AR system. The first pass tracks camera poses timely at video rate, which allows the reconstruction results be updated and visualized correspondingly during the scanning. The second pass takes place simultaneously to handle occlusion between virtual objects and real scene according to camera pose. Finally, the render results of virtual objects and the color images are fused to generate AR contents. Our results indicate that this method is stable and precise for occlusion handling, and can effectively improve realism in AR system.

This is the first of our two accepted papers in this conference so we are presenting it as Part 1 in the new and growing field known as Water-HCI or WaterHCI (Water-Human-Computer Interface/Interaction/Intersection). WaterHCI originated in the 1960s and 1970s as a form of water interaction, water monitoring, water-based augmented reality / extended reality, and the like. Much of this work began with hydraulophones (underwater musical instruments) in the 1960s and underwater Augmented Reality (AR) or eXtended Reality (XR) with the SWIM (Sequential Wave Imprinting Machine) in the 1970s. SWIM is a sensing and meta-sensing (sensing-of-sensing) tool with real-world applications in the XR visualization of otherwise invisible phenomena. In this paper, SWIM is applied to understanding open water, such as at beaches, to realtime understanding of water characteristics, and their spatial variations. A sensor and meta-sensor pod was developed and can be towed behind a swimmer to provide immediate XR feedback of the current water characteristics to enable the swimmer to choose an optimal path to swim. Part 2 of WaterHCI was also developed based on autonomous crafts, drones, and the like to sense water quality and generate an XR "heatmap" that shows spatial variations of water properties such as water temperature, turbidity, conductivity, etc., made visible to a swimmer’s head-up display in realtime.

AR/VR assisted integrated framework of autonomous disassembly system for industrial products

Augmented Reality (AR) is the process of integrating virtual elements in reality, often by mixing computer graphics into a live video stream of a real scene. It requires registration of the target object with respect to the cameras. To this end, some approaches rely on dedicated hardware, such as magnetic trackers or infra-red cameras, but they are too expensive and cumbersome to reach a large public. Others are based on specifically designed markers which usually look like bar-codes. However, they alter the look of objects to be augmented, thereby hindering their use in application for which visual design matters. Recent advances in Computer Vision have made it possible to track and detect objects by relying on natural features. However, no such method is commonly used in the AR community, because the maturity of available packages is not sufficient yet. As far as deformable surfaces are concerned, the choice is even more limited, mainly because initialization is so difficult. Our main contribution is therefore a new AR framework that can properly augment deforming surfaces in real-time. Its target platform is a standard PC and a single webcam. It does not require any complex calibration procedure, making it perfectly suitable for novice end-users. To satisfy to the most demanding application designers, our framework does not require any scene engineering, renders virtual objects illuminated by real light, and let real elements occlude virtual ones. To meet this challenge, we developed several innovative techniques. Our approach to real-time registration of a deforming surface is based on wide-baseline feature matching. However, traditional outlier elimination techniques such as RANSAC are unable to handle the non-rigid surface's large number of degrees of freedom. We therefore proposed a new robust estimation scheme that allows both 2–D and 3–D non-rigid surface registration. Another issue of critical importance in AR to achieve realism is illumination handling, for which existing techniques often require setup procedures or devices such as reflective spheres. By contrast, our framework includes methods to estimate illumination for rendering purposes without sacrificing ease of use. Finally, several existing approaches to handling occlusions in AR rely on multiple cameras or can only deal with occluding objects modeled beforehand. Our requires only one camera and models occluding objects at runtime. We incorporated these components in a consistent and flexible framework. We used it to augment many different objects such as a deforming T-shirt or a sheet of paper, under challenging conditions, in real-time, and with correct handling of illumination and occlusions. We also used our non-rigid surface registration technique to measure the shape of deformed sails. We validated the ease of deployment of our framework by distributing a software package and letting an artist use it to create two AR applications.

Grounded in the Technology Acceptance Model, Flow Theory, and Diffusion of Innovation, this paper explores the psychological indicators of Augmented Reality (AR)-enabled e-commerce adoption among Gen Z in India. It studies the direct effects of trust, compatibility, enjoyment, usefulness, ease of use, and AR perception on the intention to use such a platform. Additionally, we identify each variable's normalized relative relevance and the essential factors driving adoption. Criterion-based purposive sampling was employed to collect data from Gen Z e-commerce users across India. 658 usable responses were collected over three months. The dataset was analyzed using Partial Least Squares Structural Equation Modelling, Artificial Neural Networks, and Necessary Condition Analysis. The analysis revealed that enjoyment and compatibility are the strongest predictors of AR adoption, ranked first and second, respectively, and are a must-have with a medium effect size. Following that, ease of use and AR perception establish a significant relationship and are found to be moderately necessary. Remarkably, while trust and usefulness are statistically significant, they rank the lowest, indicating that they are foundational but not top predictors. Previous research focused on features specific to AR instead of fully grasping genuine user interaction. This research closes a significant gap in the academic discourse by providing a model for AR adoption in a developing market with factors that account for users' interaction with AR features. Investing in gamified, high-quality, and realistic AR experiences and alignment to users' lifestyles can drive adoption, leading to customer retention and loyalty.

Augmented reality (AR) adoption in archeological site museums has attracted growing attention; however, a notable gap remains in understanding how personal traits and technological perceptions interact to influence tourists’ choices. To address this gap, this study conducted at the Sanxingdui Archeological Site Museum employs the Technology Acceptance Model (TAM), a widely used framework for analyzing user acceptance of technology, alongside structural equation modeling to examine the nuanced interplay of Technology Readiness dimensions and their impact on perceptions. The findings reveal that optimism does not significantly influence attitudes toward AR, while innovativeness has a positive effect. Discomfort is negatively associated with AR attitudes, while perceived security concerns have a counterintuitive positive effect. Moreover, perceived ease of use strongly determines the perceived usefulness of AR, which, in turn, directly influences attitudes toward the technology. Perceived ease of use also plays a crucial role in shaping AR attitudes. Additionally, a positive attitude toward AR is strongly linked to future adoption intentions, which, in turn, significantly correlate with tourists’ intentions to visit destinations. These insights not only enhance academic discussions on TAM and AR in tourism but also offer valuable practical implications for the museum sector seeking seamless AR integration.

Augmented reality (AR) is an emerging technology in microsurgery for free flap reconstruction. AR allows surgeons to superimpose preoperative CT images onto the patient, providing real-time insight into the underlying anatomy and aiding in the decision-making process; however, there is limited empirical evidence supporting the effectiveness of this modality. We conducted a systematic review to investigate whether the use of AR devices in free flap reconstruction correlates with improved outcomes. A comprehensive search of PubMed, Embase, and Scopus was performed on February 19, 2025. Our search included retrospective and prospective articles that demonstrated the use of AR technology intraoperatively and reported surgical outcomes in any type of free flap reconstruction. The initial search yielded 158 articles, with 8 ultimately included in the study. Articles were reviewed for technical accuracy, surgeon ease of use, operative time, complications, and operative costs. AR can guide surgeons, particularly those with less experience. As surgeons gain a better understanding of perforator locations, they operate with increased confidence and efficiency. AR outperformed Doppler ultrasound in perforator identification, demonstrating higher accuracy during flap planning and dissection. The time required to harvest flaps was significantly shorter when AR was used compared to traditional flap dissection techniques. Compared to computer-aided design and computer-aided manufacturing (CAD/CAM) navigation systems, AR surgical guidance exhibited greater accuracy and required significantly less time for flap design. AR devices surpassed cutting guides in various aspects, including cost savings, reduced preparation time, increased flexibility in surgical plan modification, intraoperative tissue drift, and a more favorable effect on hand-eye coordination. No conclusive postoperative complications were reported. The majority of the literature about AR in free flap surgery comes from small clinical studies. Widescale, multi-center studies are necessary to determine the true clinical impact of AR technology in microsurgery.

Context awareness, user friendliness, and interactivity are very important and powerful concepts in building useful teaching/learning environments for the benefit of mankind. Advancements in technology are enabling us to look at new use cases in the methods of teaching, information sharing, knowledge dissemination, and self-learning. Learning environments are not only for teaching things to people., but also for providing more information to them on any subject that they may require from time to time. User friendliness can be enhanced with clever use of sensors to give hands free interactivity with the devices/gadgets. Context aware applications require sensors to get the context information. Mobile devices like smart phones and tablets today come with a hand full of sensors mounted on them which include one or two cameras, a microphone, a touch screen, an accelerometer to sense motion, and in addition have GPS and digital compass to provide location information to applications requiring these sensory inputs. The computational power packed in the processors used in these devices/gadgets including special support for graphics processing, the near general purpose computer like operating system environments, and the quality of cameras available, are all enabling application developers to map some serious computer vision based applications on today's mobile devices. This reality has encouraged us to get into development of Augmented Reality (AR) based interactive learning environments on mobile devices, leading to our development of a software framework for AR applications development and also development of an AR book and an AR board. AR has been called the eighth mass medium, after print, recordings, cinema, radio, television, Internet and mobile phones. There is ample scope for enhancing the learning/teaching experiences of the users with AR based learning environments. AR makes learning more effective and an enjoyable experience by providing more realistic information with the use of 3D graphics and animated models.

This study explores the acceptance of augmented reality (AR) in safety classes using the Technology Acceptance Model (TAM). Participants from safety classes were exposed to AR-based activities, and their perceptions of AR's usefulness and ease of use were measured through surveys. The findings reveal that participants found AR highly useful in enhancing safe learning experiences, visualizing safety procedures, and facilitating engagement. Participants also reported that AR applications were intuitive and user-friendly. The study supports the TAM model, indicating that perceived usefulness and ease of use strongly influenced participants' attitudes and intentions toward AR. Educators should prioritize emphasizing usefulness and ease of use to promote successful integration of AR in safety education.

The need for preservation and flexible exploration of historical artifacts generated increasing interest in using digital technologies in the cultural heritage context. This paper presents user interaction applications of a recent digital cultural heritage conservation and exploration project concerning one of the most famous heritage site “Gobeklitepe” in Turkey that is the oldest known human-made religious structure and added to the UNESCO’s World Heritage List by the year 2018 is 15 km away of northeast of the town Sanliurfa. The project aims at enriching the visitor experience through modern digital technologies. Main modules include 3D scanning of the artifacts, information screen and mobile interaction with Augmented Reality (AR). AR has been developed to provide information about destinations and attractions. Because of the development of AR, tourists using AR can gain valuable experience without a tourist guide. There two aims of this study: 1) is to describe acceptance of a new technology such as AR and visiting intention for visitors who use AR at a heritage destination, 2) to measure tourists’ experiences of visiting historic sites. For this purpose, two scales were used for data collection. In accordance with the first aim of the study, the scale adapted by Chung, Han & Joun (2015) which is to explain visitors’ acceptance of AR based on the TAM. Secondly, Lee & Smith’s (2015) multiple-item scale was used to measure tourists’ experiences of visiting historic sites and museums. There are three dimensions in the first scale as perceived usefulness (5 items), perceived ease of use (3 items) and visit intention (2 items) visit intention (2 items) in accordance with the purpose of the study. On the other hand, the second scale involves natively 16 items under six dimensions. The findings offer important practical implications for historic sites and museums in relation to AR and experiential marketing. The findings show that the Augmented Reality applications have an important practical usefulness for the Gobeklitepe archeological site and particularly enriching of the visitor experience. The study shows that the AR applications impact on the visit intention of the visitors. The study is revealed that applications can be applied to enhance the attractiveness of the archeological sites, as Gobeklitepe, in many destinations.

In this study, an efficient augmented reality (AR) system is developed to real-time detect and extract boundary of the target using lightweight deep learning models MobileNet and Unity Sentis, for resource constrained devices. The system integrates optimized model inference, video input and smooth AR content rendering, and enhances the efficiency of the operation while ensuring accuracy through techniques like quantization and pruning. The result shows that the system can detect objects with a mean accuracy (mAP) of 72.3%, with an intersection-to-integration ratio (IoU) of 0.85 and an average inference time of 35ms on smartphones and 20ms on PCs, which guarantees that the AR interactions are smooth and that the system is stable at 25 FPS and 45 FPS respectively. This technology can be applied in many sectors including gaming, industrial monitoring and education and many others. Although there is much work to be done in complex environments and low-end devices, this research provides a foundation for developing real-time scalable AR solutions. Future work will be directed towards extending the study to include multimodal data fusion, advanced models and more complex application scenarios.

Real-time performance is critical for Augmented Reality (AR) systems as it directly affects responsiveness and enables the timely rendering of virtual content superimposed on real scenes. In this context, we present the DARLENE wearable AR system, analysing its specifications, overall architecture and core algorithmic components. DARLENE comprises AR glasses and a wearable computing node responsible for several time-critical computation tasks. These include computer vision modules developed for the real-time analysis of dynamic scenes supporting functionalities for instance segmentation, tracking and pose estimation. To meet real-time requirements in limited resources, concrete algorithmic adaptations and design choices are introduced. The proposed system further supports real-time video streaming and interconnection with external IoT nodes. To improve user experience, a novel approach is proposed for the adaptive rendering of AR content by considering the user’s stress level, the context of use and the environmental conditions for adjusting the level of presented information towards enhancing their situational awareness. Through extensive experiments, we evaluate the performance of individual components and end-to-end pipelines. As the proposed system targets time-critical security applications where it can be used to enhance police officers’ situational awareness, further experimental results involving end users are reported with respect to overall user experience, workload and evaluation of situational awareness.

Purpose: This study explores the impact of augmented reality (AR) technology on purchase intention in Indonesia. By integrating the AR experience framework with an extended Technology Acceptance Model (TAM), the research examines how five dimensions of the AR experience—sensory experience (SE), emotional experience (EE), thinking experience (TE), action experience (AE), and related experience (RE)—affect perceived ease of use (PEOU) and perceived usefulness (PU), which subsequently influence purchase intention (PI), with attitudinal ambivalence (AA) as a mediating factor.Method: A quantitative, cross-sectional survey was conducted with 300 Indonesian respondents, aged 18 to 60, who were recent users of the AR Sephora Virtual Artist. Data were collected through an online questionnaire and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM).Result: Findings reveal that the dimensions of the AR experience positively impact PEOU and PU, which subsequently negatively influence AA. PU also directly fosters positive PI, while PEOU does not. Importantly, AA negatively affects PI, underscoring its critical role in consumer decision-making.Practical Implications for Economic Growth and Development: This research offers valuable insights for retailers to optimize AR implementation, thereby enhancing consumer engagement and driving purchase intention. Improving AR usability and effectiveness can reduce consumer uncertainty, strengthen market adoption, and advance digital commerce in the beauty industry.Originality/Value: This study uniquely integrates AA into existing AR adoption models and combines the AR experience framework with an extended TAM, providing novel theoretical contributions to AR in retail and insights into consumer behavior.