Virtual Reality Intelligent Hardware最新文献_第4页

ILIDViz: An Incremental Learning-Based Visual Analysis System for Network Anomaly Detection ILIDViz：基于增量学习的网络异常检测可视分析系统

Virtual Reality Intelligent Hardware Pub Date : 2023-12-01 DOI: 10.1016/j.vrih.2023.06.009

Xuefei Tian, Zhiyuan Wu, JunXiang Cao, Shengtao Chen, Xiaoju Dong

{"title":"ILIDViz: An Incremental Learning-Based Visual Analysis System for Network Anomaly Detection","authors":"Xuefei Tian, Zhiyuan Wu, JunXiang Cao, Shengtao Chen, Xiaoju Dong","doi":"10.1016/j.vrih.2023.06.009","DOIUrl":"10.1016/j.vrih.2023.06.009","url":null,"abstract":"<div><h3>Background</h3><p>With the development of information technology, network traffic logs mixed with various kinds of cyber-attacks have grown explosively. Traditional intrusion detection systems (IDS) have limited ability to discover new inconstant patterns and identify malicious traffic traces in real-time. It is urgent to implement more effective intrusion detection technologies to protect computer security.</p></div><div><h3>Methods</h3><p>In this paper, we design a hybrid IDS, combining our incremental learning model (KAN-SOINN) and active learning, to learn new log patterns and detect various network anomalies in real-time.</p></div><div><h3>Results & Conclusions</h3><p>The experimental results on the NSLKDD dataset show that the KAN-SOINN can be improved continuously and detect malicious logs more effectively. Meanwhile, the comparative experiments prove that using a hybrid query strategy in active learning can improve the model learning efficiency.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":"5 6","pages":"Pages 471-489"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096579623000372/pdf?md5=4b6332c477d34f662bbd8d1f6d5110ea&pid=1-s2.0-S2096579623000372-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139024181","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}

引用次数: 0

An image defocus deblurring method based on gradient difference of boundary neighborhood 基于边界邻域梯度差的图像散焦去模糊方法

Virtual Reality Intelligent Hardware Pub Date : 2023-12-01 DOI: 10.1016/j.vrih.2023.06.008

Junjie TAO , Yinghui WANG , Haomiao M.A , Tao YAN , Lingyu AI , Shaojie ZHANG , Wei LI

{"title":"An image defocus deblurring method based on gradient difference of boundary neighborhood","authors":"Junjie TAO , Yinghui WANG , Haomiao M.A , Tao YAN , Lingyu AI , Shaojie ZHANG , Wei LI","doi":"10.1016/j.vrih.2023.06.008","DOIUrl":"10.1016/j.vrih.2023.06.008","url":null,"abstract":"<div><h3>Background</h3><p>For static scenes with multiple depth layers, the existing defocused image deblurring methods have the problems of edge ringing artifacts or insufficient deblurring degree due to inaccurate estimation of blur amount, In addition, the prior knowledge in non blind deconvolution is not strong, which leads to image detail recovery challenge.</p></div><div><h3>Methods</h3><p>To this end, this paper proposes a blur map estimation method for defocused images based on the gradient difference of the boundary neighborhood, which uses the gradient difference of the boundary neighborhood to accurately obtain the amount of blurring, thus preventing boundary ringing artifacts. Then, the obtained blur map is used for blur detection to determine whether the image needs to be deblurred, thereby improving the efficiency of deblurring without manual intervention and judgment. Finally, a non blind deconvolution algorithm is designed to achieve image deblurring based on the blur amount selection strategy and sparse prior.</p></div><div><h3>Results</h3><p>Experimental results show that our method improves PSNR and SSIM by an average of 4.6% and 7.3%, respectively, compared to existing methods.</p></div><div><h3>Conclusions</h3><p>Experimental results show that our method outperforms existing methods. Compared with existing methods, our method can better solve the problems of boundary ringing artifacts and detail information preservation in defocused image deblurring.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":"5 6","pages":"Pages 538-549"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096579623000402/pdf?md5=e25f0d04bda463effe6c2d3480b7f3ad&pid=1-s2.0-S2096579623000402-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139022286","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}

引用次数: 0

RealFuVSR: Feature Enhanced Real-World Video Super-Resolution RealFuVSR：功能增强型真实世界视频超分辨率

Virtual Reality Intelligent Hardware Pub Date : 2023-12-01 DOI: 10.1016/j.vrih.2023.06.006

Zhi Li , Xiong Pang , Yiyue Jiang , Yujie Wang

{"title":"RealFuVSR: Feature Enhanced Real-World Video Super-Resolution","authors":"Zhi Li , Xiong Pang , Yiyue Jiang , Yujie Wang","doi":"10.1016/j.vrih.2023.06.006","DOIUrl":"10.1016/j.vrih.2023.06.006","url":null,"abstract":"<div><h3>Background</h3><p>The recurrent recovery is one of the common methods for video super-resolution, which models the correlation between frames via hidden states. However, when we apply the structure to real-world scenarios, it leads to unsatisfactory artifacts. We found that, in the real-world video super-resolution training, the use of unknown and complex degradation can better simulate the degradation process of the real world.</p></div><div><h3>Methods</h3><p>Based on this, we propose the RealFuVSR model, which simulates the real-world degradation and mitigates the artifacts caused by the video super-resolution. Specifically, we propose a multi-scale feature extraction module(MSF) which extracts and fuses features from multiple scales, it facilitates the elimination of hidden state artifacts. In order to improve the accuracy of hidden states alignment information, RealFuVSR use advanced optical flow-guided deformable convolution. Besides, cascaded residual upsampling module is used to eliminate the noise caused by the upsampling process.</p></div><div><h3>Results</h3><p>The experiment demonstrates that our RealFuVSR model can not only recover the high-quality video but also outperform the state-of-the-art RealBasicVSR and RealESRGAN models.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":"5 6","pages":"Pages 523-537"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096579623000396/pdf?md5=ccc376bebb752e8cce7b3633ad69bf64&pid=1-s2.0-S2096579623000396-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139012746","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}

引用次数: 0

Opening Design using Bayesian Optimization 利用贝叶斯优化进行开局设计

Virtual Reality Intelligent Hardware Pub Date : 2023-12-01 DOI: 10.1016/j.vrih.2023.06.001

Nick Vitsas, Iordanis Evangelou, Georgios Papaioannou, Anastasios Gkaravelis

引用次数: 0

PartLabeling: A Label Management Framework in 3D Space 部件标签：三维空间中的标签管理框架

Virtual Reality Intelligent Hardware Pub Date : 2023-12-01 DOI: 10.1016/j.vrih.2023.06.004

Semir Elezovikj , Jianqing Jia , Chiu C. Tan , Haibin Ling

{"title":"PartLabeling: A Label Management Framework in 3D Space","authors":"Semir Elezovikj , Jianqing Jia , Chiu C. Tan , Haibin Ling","doi":"10.1016/j.vrih.2023.06.004","DOIUrl":"10.1016/j.vrih.2023.06.004","url":null,"abstract":"<div><p>In this work, we focus on the label layout problem: specifying the positions of overlaid virtual annotations in Virtual/Augmented Reality scenarios. Designing a layout of labels that does not violate domain-specific design requirements, while at the same time satisfying aesthetic and functional principles of good design, can be a daunting task even for skilled visual designers. Presenting the annotations in 3D object space instead of projection space, allows for the preservation of spatial and depth cues. This results in stable layouts in dynamic environments, since the annotations are anchored in 3D space. In this paper we make two major contributions. First, we propose a technique for managing the layout and rendering of annotations in Virtual/Augmented Reality scenarios by manipulating the annotations directly in 3D space. For this, we make use of Artificial Potential Fields and use 3D geometric constraints to adapt them in 3D space. Second, we introduce PartLabeling: an open source platform in the form of a web application that acts as a much-needed generic framework allowing to easily add labeling algorithms and 3D models. This serves as a catalyst for researchers in this field to make their algorithms and implementations publicly available, as well as ensure research reproducibility. The PartLabeling framework relies on a dataset that we generate as a subset of the original PartNet dataset [17] consisting of models suitable for the label management task. The dataset consists of 1,000 3D models with part annotations.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":"5 6","pages":"Pages 490-508"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096579623000347/pdf?md5=057ef6e2f709bc02a8c7c5a29fd317da&pid=1-s2.0-S2096579623000347-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139025326","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}

引用次数: 0

Implementation of natural hand gestures in holograms for 3D object manipulation 在全息图中实现自然手势，用于3D对象操作

Virtual Reality Intelligent Hardware Pub Date : 2023-10-01 DOI: 10.1016/j.vrih.2023.02.001

Ajune Wanis Ismail , Muhammad Akma Iman

引用次数: 0

Survey of lightweighting methods of huge 3D models for online Web3D visualization 面向Web3D在线可视化的海量三维模型轻量化方法研究

Virtual Reality Intelligent Hardware Pub Date : 2023-10-01 DOI: 10.1016/j.vrih.2020.02.002

Xiaojun Liu , Jinyuan Jia , Chang Liu

{"title":"Survey of lightweighting methods of huge 3D models for online Web3D visualization","authors":"Xiaojun Liu , Jinyuan Jia , Chang Liu","doi":"10.1016/j.vrih.2020.02.002","DOIUrl":"https://doi.org/10.1016/j.vrih.2020.02.002","url":null,"abstract":"<div><h3>Background</h3><p>With the rapid development of Web3D technologies, the online Web3D visualization, particularly for complex models or scenes, has been in a great demand. Owing to the major conflict between the Web3D system load and resource consumption in the processing of these huge models, the huge 3D model lightweighting methods for online Web3D visualization are reviewed in this paper.</p></div><div><h3>Methods</h3><p>By observing the geometry redundancy introduced by man-made operations in the modeling procedure, several categories of lightweighting related work that aim at reducing the amount of data and resource consumption are elaborated for Web3D visualization.</p></div><div><h3>Results</h3><p>By comparing perspectives, the characteristics of each method are summarized, and among the reviewed methods, the geometric redundancy removal that achieves the lightweight goal by detecting and removing the repeated components is an appropriate method for current online Web3D visualization. Meanwhile, the learning algorithm, still in improvement period at present, is our expected future research topic.</p></div><div><h3>Conclusions</h3><p>Various aspects should be considered in an efficient lightweight method for online Web3D visualization, such as characteristics of original data, combination or extension of existing methods, scheduling strategy, cache management, and rendering mechanism. Meanwhile, innovation methods, particularly the learning algorithm, are worth exploring.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":"5 5","pages":"Pages 395-406"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71728992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deep-reinforcement-learning-based robot motion strategies for grabbing objects from human hands 基于深度强化学习的机器人从人手中抓取物体的运动策略

Virtual Reality Intelligent Hardware Pub Date : 2023-10-01 DOI: 10.1016/j.vrih.2022.12.001

Zeyuan Cai , Zhiquan Feng , Liran Zhou , Xiaohui Yang , Tao Xu

{"title":"Deep-reinforcement-learning-based robot motion strategies for grabbing objects from human hands","authors":"Zeyuan Cai , Zhiquan Feng , Liran Zhou , Xiaohui Yang , Tao Xu","doi":"10.1016/j.vrih.2022.12.001","DOIUrl":"https://doi.org/10.1016/j.vrih.2022.12.001","url":null,"abstract":"<div><h3>Background</h3><p>Robot grasping encompasses a wide range of research areas; however, most studies have been focused on the grasping of only stationary objects in a scene; only a few studies on how to grasp objects from a user's hand have been conducted. In this paper, a robot grasping algorithm based on deep reinforcement learning (RGRL) is proposed.</p></div><div><h3>Methods</h3><p>The RGRL takes the relative positions of the robot and the object in a user's hand as input and outputs the best action of the robot in the current state. Thus, the proposed algorithm realizes the functions of autonomous path planning and grasping objects safely from the hands of users. A new method for improving the safety of human–robot cooperation is explored. To solve the problems of a low utilization rate and slow convergence of reinforcement learning algorithms, the RGRL is first trained in a simulation scene, and then, the model parameters are applied to a real scene. To reduce the difference between the simulated and real scenes, domain randomization is applied to randomly change the positions and angles of objects in the simulated scenes at regular intervals, thereby improving the diversity of the training samples and robustness of the algorithm.</p></div><div><h3>Results</h3><p>The RGRL's effectiveness and accuracy are verified by evaluating it on both simulated and real scenes, and the results show that the RGRL can achieve an accuracy of more than 80% in both cases.</p></div><div><h3>Conclusions</h3><p>RGRL is a robot grasping algorithm that employs domain randomization and deep reinforcement learning for effective grasping in simulated and real scenes. However, it lacks flexibility in adapting to different grasping poses, prompting future research in achieving safe grasping for diverse user postures.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":"5 5","pages":"Pages 407-421"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71728993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Eye-shaped keyboard for dual-hand text entry in virtual reality 虚拟现实中用于双手文本输入的眼形键盘

Virtual Reality Intelligent Hardware Pub Date : 2023-10-01 DOI: 10.1016/j.vrih.2023.07.001

Kangyu Wang , Yangqiu Yan , Hao Zhang , Xiaolong Liu , Lili Wang

{"title":"Eye-shaped keyboard for dual-hand text entry in virtual reality","authors":"Kangyu Wang , Yangqiu Yan , Hao Zhang , Xiaolong Liu , Lili Wang","doi":"10.1016/j.vrih.2023.07.001","DOIUrl":"https://doi.org/10.1016/j.vrih.2023.07.001","url":null,"abstract":"<div><p>We propose an eye-shaped keyboard for high-speed text entry in virtual reality (VR), having the shape of dual eyes with characters arranged along the curved eyelids, which ensures low density and short spacing of the keys. The eye-shaped keyboard references the QWERTY key sequence, allowing the users to benefit from their experience using the QWERTY keyboard. The user interacts with an eye-shaped keyboard using rays controlled with both the hands. A character can be entered in one step by moving the rays from the inner eye regions to regions of the characters. A high-speed auto-complete system was designed for the eye-shaped keyboard. We conducted a pilot study to determine the optimal parameters, and a user study to compare our eye-shaped keyboard with the QWERTY and circular keyboards. For beginners, the eye-shaped keyboard performed significantly more efficiently and accurately with less task load and hand movement than the circular keyboard. Compared with the QWERTY keyboard, the eye-shaped keyboard is more accurate and significantly reduces hand translation while maintaining similar efficiency. Finally, to evaluate the potential of eye-shaped keyboards, we conducted another user study. In this study, the participants were asked to type continuously for three days using the proposed eye-shaped keyboard, with two sessions per day. In each session, participants were asked to type for 20min, and then their typing performance was tested. The eye-shaped keyboard was proven to be efficient and promising, with an average speed of 19.89 words per minute (WPM) and mean uncorrected error rate of 1.939%. The maximum speed reached 24.97 WPM after six sessions and continued to increase.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":"5 5","pages":"Pages 451-469"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71729298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Novel learning framework for optimal multi-object video trajectory tracking 一种新的多目标视频轨迹优化学习框架

Virtual Reality Intelligent Hardware Pub Date : 2023-10-01 DOI: 10.1016/j.vrih.2023.04.001

Siyuan Chen, Xiaowu Hu, Wenying Jiang, Wen Zhou, Xintao Ding

{"title":"Novel learning framework for optimal multi-object video trajectory tracking","authors":"Siyuan Chen, Xiaowu Hu, Wenying Jiang, Wen Zhou, Xintao Ding","doi":"10.1016/j.vrih.2023.04.001","DOIUrl":"https://doi.org/10.1016/j.vrih.2023.04.001","url":null,"abstract":"<div><h3>Background</h3><p>With the rapid development of Web3D, virtual reality, and digital twins, virtual trajectories and decision data considerably rely on the analysis and understanding of real video data, particularly in emergency evacuation scenarios. Correctly and effectively evacuating crowds in virtual emergency scenarios are becoming increasingly urgent. One good solution is to extract pedestrian trajectories from videos of emergency situations using a multi-target tracking algorithm and use them to define evacuation procedures.</p></div><div><h3>Methods</h3><p>To implement this solution, a trajectory extraction and optimization framework based on multi-target tracking is developed in this study. First, a multi-target tracking algorithm is used to extract and preprocess the trajectory data of the crowd in a video. Then, the trajectory is optimized by combining the trajectory point extraction algorithm and Savitzky–Golay smoothing filtering method. Finally, related experiments are conducted, and the results show that the proposed approach can effectively and accurately extract the trajectories of multiple target objects in real time.</p></div><div><h3>Results</h3><p>In addition, the proposed approach retains the real characteristics of the trajectories as much as possible while improving the trajectory smoothing index, which can provide data support for the analysis of pedestrian trajectory data and formulation of personnel evacuation schemes in emergency scenarios.</p></div><div><h3>Conclusions</h3><p>Further comparisons with methods used in related studies confirm the feasibility and superiority of the proposed framework.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":"5 5","pages":"Pages 422-438"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71728994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0