Virtual Reality Intelligent Hardware最新文献

{"title":"Chasing in virtual environment:Dynamic alignment for multi-user collaborative redirected walking","authors":"Tianyang Dong,&nbsp;Shuqian Lv,&nbsp;Hubin Kong,&nbsp;Huanbo Zhang","doi":"10.1016/j.vrih.2024.07.002","DOIUrl":"10.1016/j.vrih.2024.07.002","url":null,"abstract":"<div><h3>Background</h3><div>The redirected walking (RDW) method for multi-user collaboration requires maintaining the relative position between users in a virtual environment (VE) and physical environment (PE). A chasing game in a VE is a typical virtual reality game that entails multi-user collaboration. When a user approaches and interacts with a target user in the VE, the user is expected to approach and interact with the target user in the corresponding PE as well. Existing methods of multi-user RDW mainly focus on obstacle avoidance, which does not account for the relative positional relationship between the users in both VE and PE.</div></div><div><h3>Methods</h3><div>To enhance the user experience and facilitate potential interaction, this paper presents a novel dynamic alignment algorithm for multi-user collaborative redirected walking (DA-RDW) in a shared PE where the target user and other users are moving. This algorithm adopts improved artificial potential fields, where the repulsive force is a function of the relative position and velocity of the user with respect to dynamic obstacles. For the best alignment, this algorithm sets the alignment-guidance force in several cases and then converts it into a constrained optimization problem to obtain the optimal direction. Moreover, this algorithm introduces a potential interaction object selection strategy for a dynamically uncertain environment to speed up the subsequent alignment. To balance obstacle avoidance and alignment, this algorithm uses the dynamic weightings of the virtual and physical distances between users and the target to determine the resultant force vector.</div></div><div><h3>Results</h3><div>The efficacy of the proposed method was evaluated using a series of simulations and live-user experiments. The experimental results demonstrate that our novel dynamic alignment method for multi-user collaborative redirected walking can reduce the distance error in both VE and PE to improve alignment with fewer collisions.</div></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":"7 1","pages":"Pages 26-46"},"PeriodicalIF":0.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing wireless sensor network topology with node load consideration","authors":"Ruizhi Chen","doi":"10.1016/j.vrih.2024.08.003","DOIUrl":"10.1016/j.vrih.2024.08.003","url":null,"abstract":"<div><h3>Background</h3><div>With the development of the Internet, the topology optimization of wireless sensor networks has received increasing attention. However, traditional optimization methods often overlook the energy imbalance caused by node loads, which affects network performance.</div></div><div><h3>Methods</h3><div>To improve the overall performance and efficiency of wireless sensor networks, a new method for optimizing the wireless sensor network topology based on K-means clustering and firefly algorithms is proposed. The K-means clustering algorithm partitions nodes by minimizing the within-cluster variance, while the firefly algorithm is an optimization algorithm based on swarm intelligence that simulates the flashing interaction between fireflies to guide the search process. The proposed method first introduces the K-means clustering algorithm to cluster nodes and then introduces a firefly algorithm to dynamically adjust the nodes.</div></div><div><h3>Results</h3><div>The results showed that the average clustering accuracies in the Wine and Iris data sets were 86.59% and 94.55%, respectively, demonstrating good clustering performance. When calculating the node mortality rate and network load balancing standard deviation, the proposed algorithm showed dead nodes at approximately 50 iterations, with an average load balancing standard deviation of 1.7×10⁴, proving its contribution to extending the network lifespan.</div></div><div><h3>Conclusions</h3><div>This demonstrates the superiority of the proposed algorithm in significantly improving the energy efficiency and load balancing of wireless sensor networks to extend the network lifespan. The research results indicate that wireless sensor networks have theoretical and practical significance in fields such as monitoring, healthcare, and agriculture.</div></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":"7 1","pages":"Pages 47-61"},"PeriodicalIF":0.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Finger tracking for wearable VR glove using flexible rack mechanism","authors":"Roshan Thilakarathna,&nbsp;Maroay Phlernjai","doi":"10.1016/j.vrih.2024.03.001","DOIUrl":"10.1016/j.vrih.2024.03.001","url":null,"abstract":"<div><h3>Background</h3><div>With the increasing prominence of hand and finger motion tracking in virtual reality (VR) applications and rehabilitation studies, data gloves have emerged as a prevalent solution. In this study, we developed an innovative, lightweight, and detachable data glove tailored for finger motion tracking in VR environments.</div></div><div><h3>Methods</h3><div>The glove design incorporates a potentiometer coupled with a flexible rack and pinion gear system, facilitating precise and natural hand gestures for interaction with VR applications. Initially, we calibrated the potentiometer to align with the actual finger bending angle, and verified the accuracy of angle measurements recorded by the data glove. To verify the precision and reliability of our data glove, we conducted repeatability testing for flexion (grip test) and extension (flat test), with 250 measurements each, across five users. We employed the Gage Repeatability and Reproducibility to analyze and interpret the repeatable data. Furthermore, we integrated the gloves into a SteamVR home environment using the OpenGlove auto-calibration tool.</div></div><div><h3>Conclusions</h3><div>The repeatability analysis revealed an aggregate error of 1.45 degrees in both the gripped and flat hand positions. This outcome was notably favorable when compared with the findings from assessments of nine alternative data gloves that employed similar protocols. In these experiments, users navigated and engaged with virtual objects, underlining the glove's exact tracking of finger motion. Furthermore, the proposed data glove exhibited a low response time of 17–34 ms and back-drive force of only 0.19 N. Additionally, according to a comfort evaluation using the Comfort Rating Scales, the proposed glove system is wearable, placing it at the WL1 level.</div></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":"7 1","pages":"Pages 1-25"},"PeriodicalIF":0.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FDCPNet:feature discrimination and context propagation network for 3D shape representation","authors":"Weimin SHI,&nbsp;Yuan XIONG,&nbsp;Qianwen WANG,&nbsp;Han JIANG,&nbsp;Zhong ZHOU","doi":"10.1016/j.vrih.2024.06.001","DOIUrl":"10.1016/j.vrih.2024.06.001","url":null,"abstract":"<div><h3>Background</h3><div>Three-dimensional (3D) shape representation using mesh data is essential in various applications, such as virtual reality and simulation technologies. Current methods for extracting features from mesh edges or faces struggle with complex 3D models because edge-based approaches miss global contexts and face-based methods overlook variations in adjacent areas, which affects the overall precision. To address these issues, we propose the Feature Discrimination and Context Propagation Network (FDCPNet), which is a novel approach that synergistically integrates local and global features in mesh datasets.</div></div><div><h3>Methods</h3><div>FDCPNet is composed of two modules: (1) the Feature Discrimination Module, which employs an attention mechanism to enhance the identification of key local features, and (2) the Context Propagation Module, which enriches key local features by integrating global contextual information, thereby facilitating a more detailed and comprehensive representation of crucial areas within the mesh model.</div></div><div><h3>Results</h3><div>Experiments on popular datasets validated the effectiveness of FDCPNet, showing an improvement in the classification accuracy over the baseline MeshNet. Furthermore, even with reduced mesh face numbers and limited training data, FDCPNet achieved promising results, demonstrating its robustness in scenarios of variable complexity.</div></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":"7 1","pages":"Pages 83-94"},"PeriodicalIF":0.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A haptic feedback glove for virtual piano interaction","authors":"Yifan FU,&nbsp;Jialin LIU,&nbsp;Xu LI,&nbsp;Xiaoying SUN","doi":"10.1016/j.vrih.2024.07.001","DOIUrl":"10.1016/j.vrih.2024.07.001","url":null,"abstract":"<div><h3>Background</h3><div>Haptic feedback plays a crucial role in virtual reality (VR) interaction, helping to improve the precision of user operation and enhancing the immersion of the user experience. Instrumental haptic feedback in virtual environments is primarily realized using grounded force or vibration feedback devices. However, improvements are required in terms of the active space and feedback realism.</div></div><div><h3>Methods</h3><div>We propose a lightweight and flexible haptic feedback glove that can haptically render objects in VR environments via kinesthetic and vibration feedback, thereby enabling users to enjoy a rich virtual piano-playing experience. The kinesthetic feedback of the glove relies on a cable-pulling mechanism that rotates the mechanism and pulls the two cables connected to it, thereby changing the amount of force generated to simulate the hardness or softness of the object. Vibration feedback is provided by small vibration motors embedded in the bottom of the fingertips of the glove. We designed a piano-playing scenario in the virtual environment and conducted user tests. The evaluation metrics were clarity, realism, enjoyment, and satisfaction.</div></div><div><h3>Results</h3><div>A total of 14 subjects participated in the test, and the results showed that our proposed glove scored significantly higher on the four evaluation metrics than the no-feedback and vibration feedback methods.</div></div><div><h3>Conclusions</h3><div>Our proposed glove significantly enhances the user experience when interacting with virtual objects.</div></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":"7 1","pages":"Pages 95-110"},"PeriodicalIF":0.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"YGC-SLAM:A visual SLAM based on improved YOLOv5 and geometric constraints for dynamic indoor environments","authors":"Juncheng ZHANG ,&nbsp;Fuyang KE ,&nbsp;Qinqin TANG ,&nbsp;Wenming YU ,&nbsp;Ming ZHANG","doi":"10.1016/j.vrih.2024.05.001","DOIUrl":"10.1016/j.vrih.2024.05.001","url":null,"abstract":"<div><h3>Background</h3><div>As visual simultaneous localization and mapping (SLAM) is primarily based on the assumption of a static scene, the presence of dynamic objects in the frame causes problems such as a deterioration of system robustness and inaccurate position estimation. In this study, we propose a YGC-SLAM for indoor dynamic environments based on the ORB-SLAM2 framework combined with semantic and geometric constraints to improve the positioning accuracy and robustness of the system.</div></div><div><h3>Methods</h3><div>First, the recognition accuracy of YOLOv5 was improved by introducing the convolution block attention model and the improved EIOU loss function, whereby the prediction frame converges quickly for better detection. The improved YOLOv5 was then added to the tracking thread for dynamic target detection to eliminate dynamic points. Subsequently, multi-view geometric constraints were used for re-judging to further eliminate dynamic points while enabling more useful feature points to be retained and preventing the semantic approach from over-eliminating feature points, causing a failure of map building. The K-means clustering algorithm was used to accelerate this process and quickly calculate and determine the motion state of each cluster of pixel points. Finally, a strategy for drawing keyframes with de-redundancy was implemented to construct a clear 3D dense static point-cloud map.</div></div><div><h3>Results</h3><div>Through testing on TUM dataset and a real environment, the experimental results show that our algorithm reduces the absolute trajectory error by 98.22% and the relative trajectory error by 97.98% compared with the original ORB-SLAM2, which is more accurate and has better real-time performance than similar algorithms, such as DynaSLAM and DS-SLAM.</div></div><div><h3>Conclusions</h3><div>The YGC-SLAM proposed in this study can effectively eliminate the adverse effects of dynamic objects, and the system can better complete positioning and map building tasks in complex environments.</div></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":"7 1","pages":"Pages 62-82"},"PeriodicalIF":0.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Survey of neurocognitive disorder detection methods based on speech, visual, and virtual reality technologies","authors":"Tian ZHENG ,&nbsp;Xinheng WANG ,&nbsp;Xiaolan PENG ,&nbsp;Ning SU ,&nbsp;Tianyi XU ,&nbsp;Xurong XIE ,&nbsp;Jin HUANG ,&nbsp;Lun XIE ,&nbsp;Feng TIAN","doi":"10.1016/j.vrih.2024.08.001","DOIUrl":"10.1016/j.vrih.2024.08.001","url":null,"abstract":"<div><div>The global trend of population aging poses significant challenges to society and healthcare systems, particularly because of neurocognitive disorders (NCDs) such as Parkinson's disease (PD) and Alzheimer's disease (AD). In this context, artificial intelligence techniques have demonstrated promising potential for the objective assessment and detection of NCDs. Multimodal contactless screening technologies, such as speech-language processing, computer vision, and virtual reality, offer efficient and convenient methods for disease diagnosis and progression tracking. This paper systematically reviews the specific methods and applications of these technologies in the detection of NCDs using data collection paradigms, feature extraction, and modeling approaches. Additionally, the potential applications and future prospects of these technologies for the detection of cognitive and motor disorders are explored. By providing a comprehensive summary and refinement of the extant theories, methodologies, and applications, this study aims to facilitate an in-depth understanding of these technologies for researchers, both within and outside the field. To the best of our knowledge, this is the first survey to cover the use of speech-language processing, computer vision, and virtual reality technologies for the detection of NSDs.</div></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":"6 6","pages":"Pages 421-472"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143315199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Previs-Real:Interactive virtual previsualization system for news shooting rehearsal and evaluation","authors":"Che Qu ,&nbsp;Shaocong Wang ,&nbsp;Chao Zhou ,&nbsp;Tongchen Zhao ,&nbsp;Rui Guo ,&nbsp;Cheng Wa Wong ,&nbsp;Chi Deng ,&nbsp;Bin Ji ,&nbsp;Yuhui Wen ,&nbsp;Yuanchun Shi ,&nbsp;Yong-Jin Liu","doi":"10.1016/j.vrih.2024.12.001","DOIUrl":"10.1016/j.vrih.2024.12.001","url":null,"abstract":"<div><h3>Background</h3><div>In the demanding field of live news broadcasting, the intricate studio production procedures and tight schedules pose significant challenges for physical rehearsals by cameramen. This paper explores the design and implementation of a lightweight virtual news previsualization system, leveraging virtual production technology and interaction design methods to address the lack of fidelity in presentations and manipulations, and the quantitative feedback of rehearsal effects in previous virtual approaches.</div></div><div><h3>Methods</h3><div>Our system, Previs-Real, is informed by user investigation with professional cameramen and studio technicians, and adheres to principles of high fidelity, accurate replication of actual hardware operations, and real-time feedback on rehearsal results. The system's software and hardware development are implemented based on Unreal Engine and accompanying toolsets, incorporating cutting-edge modeling and camera calibration methods.</div></div><div><h3>Results</h3><div>We validated Previs-Real through a user study, demonstrating superior performance in previsualization shooting tasks using the virtual system compared to traditional camera setups. The findings, supported by both objective performance metrics and subjective responses, underline Previs-Real's effectiveness and potential in transforming news broadcasting rehearsals.</div></div><div><h3>Conclusions</h3><div>Previs-Real eliminates the requirement for complex equipment interconnections and team coordination inherent in a physical studio by implementing methodologies complying the above principles, objectively resulting in a lightweight design of applicable version of virtual news previsualization system. It offers a novel solution to the challenges in news studio previsualization by focusing on key operational features rather than full environment replication. This design approach is equally effective in the process of designing lightweight systems in other fields.</div></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":"6 6","pages":"Pages 527-549"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143315910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MatStick: Changing the material sensation of objects upon impact","authors":"Songxian Liu,&nbsp;Jian He,&nbsp;Shengsheng Jiang,&nbsp;Ziyan Zhang,&nbsp;Mengfei Lv","doi":"10.1016/j.vrih.2024.11.001","DOIUrl":"10.1016/j.vrih.2024.11.001","url":null,"abstract":"<div><div>An increasing number of studies have focused on providing rich tactile feedback in virtual reality interactive scenarios. In this study, we addressed a tapping scenario in virtual reality by designing MatStick, a solution capable of offering diverse tapping sensations. MatStick utilizes a soft physical base to provide force feedback and modulates the instantaneous vibration of the base using a voice coil motor, thereby altering the perception of the base material. We conducted two psychophysical experiments and a subjective evaluation to assess the capabilities of MatStick. The results demonstrate that MatStick can deliver rich tapping sensations. Although users may find it challenging to directly correlate the tapping sensation with the actual physical material based solely on tactile feedback, in immersive scenarios combined with visual and auditory cues, MatStick significantly enhances the user's interaction experience.</div></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":"6 6","pages":"Pages 486-501"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143315200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"InputJump: Augmented reality-facilitated cross-device input fusion based on spatial and semantic information","authors":"Xin Zeng ,&nbsp;Xiaoyu Wang ,&nbsp;Tengxiang Zhang ,&nbsp;Yukang Yan ,&nbsp;Yiqiang Chen","doi":"10.1016/j.vrih.2024.10.001","DOIUrl":"10.1016/j.vrih.2024.10.001","url":null,"abstract":"<div><div>The proliferation of computing devices requires seamless cross-device interactions. Augmented reality (AR) headsets can facilitate interactions with existing computers owing to their user-centered views and natural inputs. In this study, we propose InputJump, a user-centered cross-device input fusion method that maps multi-modal cross-device inputs to interactive elements on graphical interfaces. The input jump calculates the spatial coordinates of the input target positions and the interactive elements within the coordinate system of the AR headset. It also extracts semantic descriptions of inputs and elements using large language models (LLMs). Two types of information from different inputs (e.g., gaze, gesture, mouse, and keyboard) were fused to map onto an interactive element. The proposed method is explained in detail and implemented on both an AR headset and a desktop PC. We then conducted a user study and extensive simulations to validate our proposed method. The results showed that InputJump can accurately associate a fused input with the target interactive element, enabling a more natural and flexible interaction experience.</div></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":"6 6","pages":"Pages 502-526"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143315912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}