With continued technological innovations in the fields of mixed reality (MR), wearable type MR devices, such as head-mounted display (HMD), have been released and are frequently used in various fields, such as entertainment, training, education, and shopping. However, because each product has different parts and specifications in terms of design and manufacturing process, users feel that the virtual objects overlaying real environments in MR are visualized differently, depending on the scale and color used by the MR device. In this paper, we compare the effect of scale and color parameters on users’ perceptions in using different types of MR devices to improve their MR experiences in real life. We conducted two experiments (scale and color), and our experimental study showed that the subjects who participated in the scale perception experiment clearly tended to underestimate virtual objects, in comparison with real objects, and overestimated color in MR environments.
Indoor positioning and tracking technology perform important functions in augmented reality, smart factories, and autonomous driving. The indoor positioning method using a Bluetooth low energy (BLE) beacon has been considered challenging, owing to the deviation of the receiver signal strength indicator (RSSI) value. In this paper, we propose an indoor location tracking method by adding an algorithm to reduce differences between the actual and predicted locations of moving objects. By using synthetic data generated from actual measured values, neural networks were trained and used to predict the location of the beacon. Also, an improved tracking algorithm of moving objects was proposed by considering the angle of rotation relative to the origin. Through the simulation, it was confirmed that the improved tracking results were obtained by applying the proposed tracking algorithm to the locations predicted by neural networks. Eliminate θ i in temp_angle [1:k] endif endfor Copy temporary array temp_angle [1:k] to valid angle array valid_angle[1:k] Obtain θ e from the mean of valid_angle[1:k] Sleep for a second endwhile About the Authors Sungkwan Youm received his B.S. degree in control instrumentation engineering from
This study presents an insightful examination of the conceptual and practical facets of the Metaverse by establishing a novel theoretical framework underpinned by an empirical case study of the Sandbox platform. Anchored in the principles of legality, virtual-reality integration, technological affinity, and community-driven innovation, the paper elucidates the inherent characteristics and potentialities of the Metaverse. Through meticulous research, the paper investigates the antecedents and evolution of the Metaverse, postulating an open, decentralized, and self-regulating ecosystem predicated on user-generated content and engagement. Furthermore, an in-depth case study of the Sandbox elucidates the practical applications, challenges, and opportunities associated with the operationalization of the Metaverse. The study showcases how avant-garde technologies such as blockchain, virtual reality, and artificial intelligence are instrumental in fostering immersive experiences, safeguarding virtual asset ownership, and facilitating tailored services. Moreover, the paper accentuates the indispensable role of community engagement and continuous innovation in cultivating a flourishing Metaverse environment. The analysis exposes that the burgeoning development of the Metaverse is intrinsically linked to the amalgamation of the virtual and the tangible, extending the frontiers of the digital economy. While shedding light on the virtues of the Metaverse, the study recognizes its nascent state and encourages further scholarly inquiry to comprehend and navigate its complexities. This research contributes significantly to the academic and practical understanding of the Metaverse, serving as a cornerstone for future investigations and technological advancements in this paradigm-shifting domain.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.