Virtual Reality Intelligent Hardware最新文献

{"title":"EasyGaze: Hybrid eye tracking approach for handheld mobile devices","authors":"Shiwei Cheng,&nbsp;Qiufeng Ping,&nbsp;Jialing Wang,&nbsp;Yijian Chen","doi":"10.1016/j.vrih.2021.10.003","DOIUrl":"https://doi.org/10.1016/j.vrih.2021.10.003","url":null,"abstract":"<div><h3>Background</h3><p>Eye-tracking technology for mobile devices has made significant progress. However, owing to limited computing capacity and the complexity of context, the conventional image feature-based technology cannot extract features accurately, thus affecting the performance.</p></div><div><h3>Methods</h3><p>This study proposes a novel approach by combining appearance- and feature-based eye-tracking methods. Face and eye region detections were conducted to obtain features that were used as inputs to the appearance model to detect the feature points. The feature points were used to generate feature vectors, such as corner center-pupil center, by which the gaze fixation coordinates were calculated.</p></div><div><h3>Results</h3><p>To obtain feature vectors with the best performance, we compared different vectors under different image resolution and illumination conditions, and the results indicated that the average gaze fixation accuracy was achieved at a visual angle of 1.93° when the image resolution was 96 × 48 pixels, with light sources illuminating from the front of the eye.</p></div><div><h3>Conclusions</h3><p>Compared with the current methods, our method improved the accuracy of gaze fixation and it was more usable.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096579622000146/pdf?md5=1b38d9d1e71d71edf48eca09534dcf7b&pid=1-s2.0-S2096579622000146-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72290201","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":"Designing Generation Y Interactions: The Case of YPhone","authors":"Wei Liu","doi":"10.1016/j.vrih.2021.12.005","DOIUrl":"10.1016/j.vrih.2021.12.005","url":null,"abstract":"<div><h3>Background</h3><p>With more and more products becoming digital, mobile, and networked, paying attention to the qualities of interactions with is also getting more relevant. While interaction qualities have been addressed in several scientific studies, little attention is being paid to their implementation into a real life, everyday context. This paper describes the development of a novel office phone prototype, YPhone, which demonstrates the application of a specific set of Generation Y interaction qualities (instant, playful, collaborative, expressive, responsive, and flexible) into the context of office work. The working prototype supports office workers in experiencing new type of interactions. It is set out in practice in a series of evaluations. We found that the playful, expressive, responsive, and flexible qualities have more trust than the instant and collaborative qualities. Qualities can be grouped, although this may be different for different products that are evaluated, so researchers must be cautious about generalizing. The overall evaluation was positive with some valuable suggestions to its user interactions and features.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096579621001078/pdf?md5=37d6cba6254b5ed14bd6a4c6d9a1e4ed&pid=1-s2.0-S2096579621001078-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122669936","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":"Motivation Effect of Animated Pedagogical Agent’s Personality and Feedback Strategy Types on Learning in Virtual Training Environment","authors":"Yulong Bian","doi":"10.1016/j.vrih.2021.11.001","DOIUrl":"10.1016/j.vrih.2021.11.001","url":null,"abstract":"<div><h3>Background</h3><p>The personality and feedback of an animated pedagogical agent (APA) are vital social-emotional features that render the agent perceptually believable. The effect of them on learning in virtual training remains to be examined.</p></div><div><h3>Methods</h3><p>In this paper, an explanation model was proposed to clarify the underlying mechanism of how these two features affect learners. Two studies were conducted to investigate the model. Study 1 reexamined the effect of APA’s personality type and feedback strategy on flow experience and performance, revealing significant effects of feedback strategy on flow and performance, as well as a marginal significant effect of personality type on performance. To explore the mechanism behind these effects, a theoretical model was proposed by distinguishing between intrinsic and extrinsic motivation effect. Study 2 tested the model and round that the APA’s personality type significantly influences factors in the path of extrinsic motivation effect rather than those in the path of intrinsic motivation effect.</p></div><div><h3>Results</h3><p>By contrast, feedback strategy significantly affected factors in the path of intrinsic motivation effect.</p></div><div><h3>Conclusions</h3><p>The proposed model was supported by these results; further distinguishing the two motivation effects is necessary to understand the respective effects of an APA’s personality and feedback features on learning experiences and outcomes.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096579621000887/pdf?md5=1de5f739000f23f77f18d23f36ffc6d4&pid=1-s2.0-S2096579621000887-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129340391","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":"Navigation in virtual and real environment using brain computer interface:a progress report","authors":"Haochen Hu ,&nbsp;Yue Liu ,&nbsp;Kang Yue ,&nbsp;Yongtian Wang","doi":"10.1016/j.vrih.2021.10.002","DOIUrl":"https://doi.org/10.1016/j.vrih.2021.10.002","url":null,"abstract":"<div><p>A brain-computer interface (BCI) facilitates bypassing the peripheral nervous system and directly communicating with surrounding devices. Navigation technology using BCI has developed—from exploring the prototype paradigm in the virtual environment (VE) to accurately completing the locomotion intention of the operator in the form of a powered wheelchair or mobile robot in a real environment. This paper summarizes BCI navigation applications that have been used in both real and VEs in the past 20 years. Horizontal comparisons were conducted between various paradigms applied to BCI and their unique signal-processing methods. Owing to the shift in the control mode from synchronous to asynchronous, the development trend of navigation applications in the VE was also reviewed. The contrast between highlevel commands and low-level commands is introduced as the main line to review the two major applications of BCI navigation in real environments: mobile robots and unmanned aerial vehicles (UAVs). Finally, applications of BCI navigation to scenarios outside the laboratory; research challenges, including human factors in navigation application interaction design; and the feasibility of hybrid BCI for BCI navigation are discussed in detail.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096579622000134/pdf?md5=5a4f8528dc3cdff184c54e71eee21d0b&pid=1-s2.0-S2096579622000134-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72290203","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":"Design and Evaluation of Window Management Operations in AR Headset + Smartphone Interface","authors":"Jie Ren,&nbsp;Chun Yu,&nbsp;Yueting Weng,&nbsp;Chengchi Zhou,&nbsp;Yuanchun Shi","doi":"10.1016/j.vrih.2021.12.002","DOIUrl":"10.1016/j.vrih.2021.12.002","url":null,"abstract":"<div><h3>Background</h3><p>Combining the use of an AR headset and a smartphone can provide wider display and precise touch input simultaneously; it can redefine the way we use applications today. Unfortunately, users are deprived of such benefit because of the independence of two devices. There lacks a kind of intuitive and direct interactions across them. In this paper, we conduct a formative study to understand the window management requirements and interaction preferences of using an AR headset and a smartphone simultaneously and report the insights we gained. Also, we introduce an example vocabulary of window management operations in AR headset + smartphone interface. It allows users to manipulate windows in virtual space and shift windows between devices efficiently and seamlessly.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096579621001017/pdf?md5=d9e84d57b66e73196cd29d773375f889&pid=1-s2.0-S2096579621001017-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115876774","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":"Intelligent interaction in mixed reality","authors":"Yuanchun Shi,&nbsp;Chun Yu","doi":"10.1016/j.vrih.2022.04.001","DOIUrl":"https://doi.org/10.1016/j.vrih.2022.04.001","url":null,"abstract":"","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096579622000389/pdfft?md5=f71ead2d4b7c8f0eb9140deb859bf94b&pid=1-s2.0-S2096579622000389-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72290202","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":"3D scene graph prediction from point clouds","authors":"Fanfan Wu,&nbsp;Feihu Yan,&nbsp;Weimin Shi,&nbsp;Zhong Zhou","doi":"10.1016/j.vrih.2022.01.005","DOIUrl":"10.1016/j.vrih.2022.01.005","url":null,"abstract":"<div><h3>Background</h3><p>In this study, we propose a novel 3D scene graph prediction approach for scene understanding from point clouds.</p></div><div><h3>Methods</h3><p>It can automatically organize the entities of a scene in a graph, where objects are nodes and their relationships are modeled as edges. More specifically, we employ the DGCNN to capture the features of objects and their relationships in the scene. A Graph Attention Network (GAT) is introduced to exploit latent features obtained from the initial estimation to further refine the object arrangement in the graph structure. A one loss function modified from cross entropy with a variable weight is proposed to solve the multi-category problem in the prediction of object and predicate.</p></div><div><h3>Results</h3><p>Experiments reveal that the proposed approach performs favorably against the state-of-the-art methods in terms of predicate classification and relationship prediction and achieves comparable performance on object classification prediction.</p></div><div><h3>Conclusions</h3><p>The 3D scene graph prediction approach can form an abstract description of the scene space from point clouds.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096579622000055/pdf?md5=00217b3d733a606f1856c11825c17ba8&pid=1-s2.0-S2096579622000055-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116543976","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 Novel SSA-CCA Framework forMuscle Artifact Removal from Ambulatory EEG","authors":"Yuheng Feng ,&nbsp;Qingze Liu ,&nbsp;Aiping Liu ,&nbsp;Ruobing Qian ,&nbsp;Xun Chen","doi":"10.1016/j.vrih.2022.01.001","DOIUrl":"10.1016/j.vrih.2022.01.001","url":null,"abstract":"<div><h3>Background</h3><p>Electroencephalography (EEG) has gained popularity in various types of biomedical applications as a signal source that can be easily acquired and conveniently analyzed. However, owing to a complex scalp electrical environment, EEG is often polluted by diverse artifacts, with electromyography artifacts being the most difficult to remove. In particular, for ambulatory EEG devices with a restricted number of channels, dealing with muscle artifacts is a challenge.</p></div><div><h3>Methods</h3><p>In this study, we propose a simple but effective novel scheme that combines singular spectrum analysis (SSA) and canonical correlation analysis (CCA) algorithms for single-channel problems and then extend it to a fewchannel case by adding additional combining and dividing operations to channels.</p></div><div><h3>Results</h3><p>We evaluated our proposed framework on both semi-simulated and real-life data and compared it with some state-of-theart methods. The results demonstrate this novel framework's superior performance in both single-channel and few-channel cases.</p></div><div><h3>Conclusions</h3><p>This promising approach, based on its effectiveness and low time cost, is suitable for real-world biomedical signal processing applications.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096579622000018/pdf?md5=7a3850ea23d366350ac6e69f30e69d43&pid=1-s2.0-S2096579622000018-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116375593","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":"Giant magneto-impedance sensor with working point selfadaptation for unshielded human bio-magnetic detection","authors":"Changlin Han,&nbsp;Ming Xu,&nbsp;Jingsheng Tang,&nbsp;Yadong Liu,&nbsp;Zongtan Zhou","doi":"10.1016/j.vrih.2022.01.003","DOIUrl":"10.1016/j.vrih.2022.01.003","url":null,"abstract":"<div><h3>Background</h3><p>Compared with traditional biomagnetic field detection devices, such as superconducting quantum interference devices (SQUIDs) and atomic magnetometers, only giant magnetoimpedance (GMI) sensors can be applied for unshielded human brain biomagnetic detection, and they have the potential for application in next-generation wearable equipment for brain-computer interfaces (BCIs). Achieving a better GMI sensor without magnetic shielding requires the stimulation of the GMI effect to be maximized and environmental noise interference to be minimized. Moreover, the GMI effect stimulated in an amorphous filament is closely related to its working point, which is sensitive to both the external magnetic field and the drive current of the filament.</p></div><div><h3>Methods</h3><p>In this paper, we propose a new noisereducing GMI gradiometer with a dual-loop self-adapting structure. Noise reduction is realized by a direction-flexible differential probe, and the dual-loop structure optimizes and stabilizes the working point by automatically controlling the external magnetic field and drive current. This dual-loop structure is fully program controlled by a micro control unit (MCU), which not only simplifies the traditional constantparameter sensor circuit, saving the time required to adjust the circuit component parameters, but also improves the sensor performance and environmental adaptation.</p></div><div><h3>Results</h3><p>In the performance test, within 2 min of self-adaptation, our sensor showed a better sensitivity and signal-to-noise ratio (SNR) than those of the traditional designs and achieved a background noise of 12 pT/√Hz at 10 Hz and 7pT/√Hz at 200 Hz.</p></div><div><h3>Conclusion</h3><p>To the best of our knowledge, our sensor is the first to realize self-adaptation of both the external magnetic field and the drive current.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096579622000031/pdf?md5=0c928ff20b3f4ee53d0d5842fa3801f4&pid=1-s2.0-S2096579622000031-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"119271510","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":"Virtual-reality-based digital twin of office spaces with social distance measurement feature","authors":"Abhishek Mukhopadhyay ,&nbsp;G S Rajshekar Reddy ,&nbsp;KamalPreet Singh Saluja ,&nbsp;Subhankar Ghosh ,&nbsp;Anasol Peña-Rios ,&nbsp;Gokul Gopal ,&nbsp;Pradipta Biswas","doi":"10.1016/j.vrih.2022.01.004","DOIUrl":"10.1016/j.vrih.2022.01.004","url":null,"abstract":"<div><h3>Background</h3><p>Social distancing is an effective way to reduce the spread of the SARS-CoV-2 virus. Many students and researchers have already attempted to use computer vision technology to automatically detect human beings in the field of view of a camera and help enforce social distancing. However, because of the present lockdown measures in several countries, the validation of computer vision systems using large-scale datasets is a challenge.</p></div><div><h3>Methods</h3><p>In this paper, a new method is proposed for generating customized datasets and validating deep-learning-based computer vision models using virtual reality (VR) technology. Using VR, we modeled a digital twin (DT) of an existing office space and used it to create a dataset of individuals in different postures, dresses, and locations. To test the proposed solution, we implemented a convolutional neural network (CNN) model for detecting people in a limited-sized dataset of real humans and a simulated dataset of humanoid figures.</p></div><div><h3>Results</h3><p>We detected the number of persons in both the real and synthetic datasets with more than 90% accuracy, and the actual and measured distances were significantly correlated (<em>r</em>=0.99). Finally, we used intermittent-layer- and heatmap-based data visualization techniques to explain the failure modes of a CNN.</p></div><div><h3>Conclusions</h3><p>A new application of DTs is proposed to enhance workplace safety by measuring the social distance between individuals. The use of our proposed pipeline along with a DT of the shared space for visualizing both environmental and human behavior aspects preserves the privacy of individuals and improves the latency of such monitoring systems because only the extracted information is streamed.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096579622000043/pdf?md5=be8ce798f1ed4b70c3af4fe5572566c1&pid=1-s2.0-S2096579622000043-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45589549","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}