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2023 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2023

作者： Leng, Zhiying Wu, Shun-Cheng Li, Frederick W. B. Tombari, Federico Liang, Xiaohui Beihang University State Key Laboratory of Virtual Reality Technology and Systems China Technical University of Munich Computer Aided Medical Procedures & Augmented Reality Germany Durham University Department of Computer Science United Kingdom

ISBN: (纸本)9798350313154

Point cloud learning has gained significant attention in 3D multimedia. However, existing methods learn point-wise features in a homogeneous manner, disregarding the heterogeneity that inherently exists in point clouds. Embedding the heterogeneity into feature learning is favorable to learning more discriminative point-wise features with rich geometric structures. In this work, we are the first to analyze and utilize the heterogeneity of point clouds, namely geometric heterogeneity and category heterogeneity. We hence propose two general heterogeneous graph convolutions to exploit such heterogeneity, including Geometric Heterogeneous Graph Convolution (GHGC) and Category Heterogeneous Graph Convolution (CHGC). We implement a point heterogeneous graph neural network (PointHGN) based on classical MLP-based point cloud pipelines, without altering network configurations. Experimental results on point cloud semantic segmentation tasks manifest that our PointHGN achieves commendable performance on public datasets. Our proposed method provides an effective and alternative approach for point cloud learning that researchers can explore further. © 2023 IEEE.

关键词： Graph neural networks

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virtual Exhibition Hall as a Solution for Promoting City Profiles with the Integration of Avatars and Non-Player Characters based on Metaverse Technology 1

Virtual Exhibition Hall as a Solution for Promoting City Pro...

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1st International Conference on Technology, Engineering, and Computing Applications, ICTECA 2023

作者： Syahidi, Aulia Akhrian Kiyokawa, Kiyoshi Politeknik Negeri Banjarmasin Augmented Reality and Virtual Reality Laboratory Department of Electrical Engineering Banjarmasin Indonesia Nara Institute of Science and Technology Cybernetics and Reality Engineering Laboratory Division of Information Science Nara Ikoma Japan

ISBN: (纸本)9798350360554

In recent years, metaverse technology has become popular as a virtual environment. This has created new opportunities to showcase cities in innovative ways. This research aims to introduce MetaCityProfile, a virtual exhibition hall application that integrates avatars and intelligent Non-Player Characters (NPC) to promote city profiles using metaverse. Our focus is on the city profiles of South Kalimantan Province, Indonesia. We will also confirm the impact of the behavioral design techniques of intelligent NPCs interacting with avatars in virtual spaces. This will provide a more engaging and informative user experience. We used justification techniques to measure the impact of the application on users' knowledge and interests. Additionally, we evaluated the immersive user experience. The research results show that the use of virtual exhibition hall integrated with avatars and intelligent NPCs can significantly increase knowledge and interest in city profiles and encourage public participation. The use of metaverse provides a dynamic and engaging platform to visually promote city assets and attractions. Users report a more satisfying and immersive experience when exploring each city profile while interacting with intelligent, informative NPCs. This research provides a basis for developing more effective city promotion. © 2023 IEEE.

关键词： Smart city

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Segmentation of CAD models using hybrid representation

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虚拟现实与智能硬件(中英文) 2025年第2期7卷 188-202页

作者： Claude UWIMANA Shengdi ZHOU Limei YANG Zhuqing LI Norbelt MUTAGISHA Edouard NIYONGABO Bin ZHOU State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Peace-Bay Academy of Virtual Reality Shenyang 110004China China Aerospace Systems Engineering Corporation Beijing 100070China Department of Signal and Information Processing Beihang UniversityBeijing 100191China Department of Computer Science University of SherbrookeSherbrooke J1C0A1Canada

In this paper,we introduce an innovative method for computer-aided design(CAD)segmentation by concatenating meshes and CAD *** previous CAD segmentation methods have achieved impressive performance using single representations,such as meshes,CAD,and point ***,existing methods cannot effectively combine different three-dimensional model types for the direct conversion,alignment,and integrity maintenance of geometric and topological ***,we propose an integration approach that combines the geometric accuracy of CAD data with the flexibility of mesh representations,as well as introduce a unique hybrid representation that combines CAD and mesh models to enhance segmentation *** combine these two model types,our hybrid system utilizes advanced-neural-network techniques to convert CAD models into mesh *** complex CAD models,model segmentation is crucial for model retrieval and *** partial retrieval,it aims to segment a complex CAD model into several simple *** first component of our hybrid system involves advanced mesh-labeling algorithms that harness the digitization of CAD properties to mesh *** second component integrates labelled face features for CAD segmentation by leveraging the abundant multisemantic information embedded in CAD *** combination of mesh and CAD not only refines the accuracy of boundary delineation but also provides a comprehensive understanding of the underlying object *** study uses the Fusion 360 Gallery *** results indicate that our hybrid method can segment these models with higher accuracy than other methods that use single representations.

关键词： B-RepNet hybrid segmentation CAD models classification MeshCNN MeshCAD-Net

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Panting Traditional Musical Instruments Through virtual reality Environment with Leap Motion Control: Immersive User Experience, Usage Challenges, and Preservation Efforts

Panting Traditional Musical Instruments Through Virtual Real...

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2023 International Conference on Information Technology and Computing, ICITCOM 2023

作者： Syahidi, Aulia Akhrian Kiyokawa, Kiyoshi Augmented Reality and Virtual Reality Laboratory Department of Electrical Engineering Politeknik Negeri Banjarmasin Banjarmasin Indonesia Nara Institute of Science and Technology Cybernetics and Reality Engineering Laboratory Division of Information Science Ikorna Nara Japan

ISBN: (纸本)9798350359633

This research investigates the use of traditional musical instruments based on virtual reality (VR) with leap motion control. This technology enables users to virtually interact with Panting instruments and aims to explore immersive user experiences, challenges, and cultural preservation. We collected data through a questionnaire consisting of both open and closed questions, and analyzed the data using descriptive statistics and textual analysis. We can confirm that the proposed modern technology has the potential to promote and preserve traditional Panting musical instruments, especially for the younger generation, but alignment with cultural values and holistic education needs to be considered. In conclusion, VR technology with leap motion control promises to preserve Panting's music, but overcoming technical and cultural challenges is critical to long-term success. © 2023 IEEE.

关键词： virtual reality

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A Novel Divide and Conquer Solution for Long-term Video Salient Object Detection

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Machine Intelligence Research 2024年第4期21卷 684-703页

作者： Yun-Xiao Li Cheng-Li-Zhao Chen Shuai Li Ai-Min Hao Hong Qin State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191China College of Computer Science and Technology China University of Petroleum(East China)Qingdao 266580China Department of Computer Science Stony Brook UniversityNew York 11794USA

Recently,a new research trend in our video salient object detection(VSOD)research community has focused on enhancing the detection results via model self-fine-tuning using sparsely mined high-quality keyframes from the given *** such a learning scheme is generally effective,it has a critical limitation,i.e.,the model learned on sparse frames only possesses weak generalization *** situation could become worse on“long”videos since they tend to have intensive scene ***,in such videos,the keyframe information from a longer time span is less relevant to the previous,which could also cause learning conflict and deteriorate the model ***,the learning scheme is usually incapable of handling complex pattern *** solve this problem,we propose a divide-and-conquer framework,which can convert a complex problem domain into multiple simple ***,we devise a novel background consistency analysis(BCA)which effectively divides the mined frames into disjoint *** for each group,we assign an individual deep model on it to capture its key attribute during the fine-tuning *** the testing phase,we design a model-matching strategy,which could dynamically select the best-matched model from those fine-tuned ones to handle the given testing *** experiments show that our method can adapt severe background appearance variation coupling with object movement and obtain robust saliency detection compared with the previous scheme and the state-of-the-art methods.

关键词： Video salient object detection background consistency analysis weakly supervised learning long-term information background shift.

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A Review on Interactive Hands-free Game using BCI 16

A Review on Interactive Hands-free Game using BCI

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16th International Conference on Developments in eSystems Engineering, DeSE 2023

作者： Abuhashish, Faris Sbyrakis, George Kolivand, Hoshang Rousan, Riyadh Al Sherief, Mansour El University of Petra Animation and Multimedia Amman Jordan Liverpool John Moores University School of Computer Science and Maths Liverpool United Kingdom University of Petra Virtual and Augmented Reality Amman Jordan

ISBN: (纸本)9798350381344

This paper provides a comprehensive review of Brain-computer Interface (BCI) technology, focusing on its application in developing an interactive hands-free game for individuals with disabilities. The introduction highlights BCI's role in decoding brain signals for interaction and its potential to empower those with paralysis. The literature review traces the evolution of BCI from its inception in 1988, covering technologies like EEG and advancements in the field. It explores the development of BCI games, emphasizing their impact on motivation and neurofeedback training. The paper delves into the BCI process, classifying BCIs into dependent and independent categories, and discusses their applications in medicine, smart home control, and gaming. The concluding remarks underscore the positive influence of BCIs on various aspects of life, emphasizing the need for broader awareness and adoption of this transformative technology. © 2023 IEEE.

关键词： Assistive technology

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Approximate Supplement-Based Neighborhood Rough Set Model in Incomplete Hybrid Information Systems 20th

Approximate Supplement-Based Neighborhood Rough Set Model in...

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20th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2023

作者： Meng, Xiong Yang, Jilin Wu, Die Liu, Tang Department of Computer Science Sichuan Normal University Chengdu China Visual Computing and Virtual Reality Key Laboratory of Sichuan Province Sichuan Normal University Chengdu China

ISBN: (纸本)9789819970247

Incomplete hybrid information systems (IHISs) contain hybrid data (e.g., categorical data, numerical data) and incomplete data. With the development of big data, IHISs widely exist in various practical applications. Due to the heterogeneity of hybrid data and the complex semantics of incomplete data, effectively processing the IHIS has become a significant challenge. The established indiscernibility relations of the existing studies for dealing with IHIS over-amplify the uncertainty of missing values, which may achieve unsatisfactory results. In this paper, we propose an approximate supplement-based neighborhood rough set model (AS-NRSM) to deal with the data of IHISs. Specifically, we propose a method to approximate supplement missing values with known values or constructed interval values, and the original IHIS is becoming the constructed IHIS*. Then, we formulate a novel similarity function to construct the improved neighborhood tolerance relation and the corresponding neighborhood tolerance classes. Finally, we design two experiments on 5 UCI data sets by introducing three performance metrics. Experimental results illustrate that the proposed AS-NRSM has higher classification performance than the two representative models. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Semantics

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Advanced Deep Learning Techniques for Arabic Handwritten Digit Classification

Advanced Deep Learning Techniques for Arabic Handwritten Dig...

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Computational Intelligence Approaches and Applications (ICCIAA), International Conference on

作者： Jamal Zraqou Murad Zeer Marwan Sabateen Department of Computer Science/Virtual and Augmented Reality University of Petra Amman Jordan Faculty of Engineering and Information Technology Palestine Ahliya University Bethlehem Palestine

ISBN: (数字)9798331523657

ISBN: (纸本)9798331523664

This paper explores the application of deep learning algorithms, particularly Convolutional Neural Networks (CNNs), for Arabic handwritten digit recognition. The dataset used in this study is the Arabic Handwritten Digits Database (AHDD1), comprising 70,000 handwritten Arabic digit images, of which 60,000 were used for training and 10,000 for testing. The dataset covers digits from 0 to 9 and includes 10 samples per digit, provided by 700 contributors from diverse backgrounds, ensuring rich variability in handwriting styles. Our results indicate that deep learning models, especially CNNs, deliver strong performance in recognizing Arabic handwritten digits, achieving high accuracy. Among the tested models, simpler architectures like Multi-Layer Perceptron (MLP) and Fully Connected Neural Networks (FCNN) performed well with lower computational costs. However, the best-performing model in this study was the CNN with Data Augmentation and Dropout, which achieved the highest accuracy of 99.32%. This model demonstrates the effectiveness of advanced techniques, such as data augmentation, in enhancing the model's robustness and performance. While more complex models like ResNet provided slightly lower accuracy, they required significantly longer training times and higher computational resources. The findings underscore the importance of balancing model accuracy with computational efficiency in real-world applications. The study suggests that less complex models, enhanced with dropout regularization and batch normalization, can effectively solve Arabic handwritten digit recognition without excessive computational overhead.

关键词： Training Handwriting recognition Accuracy Computational modeling Neural networks computer architecture Data augmentation Data models Computational efficiency Convolutional neural networks

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LSBSP: A Lightweight Sharding Method of Blockchain Based on State Pruning for Efficient Data Sharing in IoMT

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computers, Materials & Continua 2025年第2期82卷 3309-3335页

作者： Guoqiong Liao Yinxiang Lei Yufang Xie Neal N.Xiong College of Virtual Reality(VR)Modern Industry Jiangxi University of Finance and EconomicsNanchang330032China School of Computer Science Jiangxi University of Traditional Chinese MedicineNanchang330004China Jiangxi Tourism&Commerce Vocational College Nanchang330100China Department of Computer Mathematical and Physical SciencesSul Ross State UniversityAlpineTX 79830USA

As the Internet of Medical Things (IoMT) continues to expand, smart health-monitoring devices generate vast amounts of valuable data while simultaneously raising critical security and privacy challenges. Blockchain technology presents a promising avenue to address these concerns due to its inherent decentralization and security features. However, scalability remains a persistent hurdle, particularly for IoMT applications that involve large-scale networks and resource-constrained devices. This paper introduces a novel lightweight sharding method tailored to the unique demands of IoMT data sharing. Our approach enhances state bootstrapping efficiency and reduces operational overhead by utilizing a dual-chain structure comprising a main chain and a snapshot chain. The snapshot chain periodically records key blockchain states, allowing nodes to synchronize more efficiently. This mechanism is critical in reducing the time and resources needed for new nodes to join the network or existing nodes to recover from outages. Additionally, a block state pruning technique is implemented, significantly minimizing storage requirements and lowering transaction execution overhead during initialization and reconfiguration processes. This is crucial given the substantial data volumes inherent in IoMT ecosystems. By adopting an optimistic sharding strategy, our model allows nodes to swiftly join the snapshot shard, while full shards retain the complete ledger history to ensure comprehensive transaction verification. Extensive evaluations across diverse shard configurations demonstrate that this method significantly outperforms existing baseline models. It provides a comprehensive solution for IoMT blockchain applications, striking an optimal balance between security, scalability, and operational efficiency.

关键词： Internet of medical things blockchain sharding lightweight snapshot

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Current Problems and Proposed Solutions for the Electronic Commerce Sector 1

Current Problems and Proposed Solutions for the Electronic C...

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1st International Conference on computer science and Emerging Technologies, CSET 2023

作者： Wahshat, Hassan Al Al-Rousan, Riyad Al-Haithami, Wafa Abdulkarem Ahmad Saany, Syarilla Iryani Mohamad, Fatma Susilawati Kumar, Rohit Ajloun National University Faculty of Business Department of Management Information System Ajloun Jordan Department of Virtual and Augmented Reality Jordan Mediu Faculty of Finance and Administrative Sciences Malaysia UniSZA Faculty of Informatics and Computing Malaysia School of Computer Science and Engineering Jain Deemed to Be University Bangalore India

ISBN: (纸本)9798350341737

The rapid growth of electronic commerce (e-commerce) has revolutionized the global business landscape, transforming the way consumers and businesses interact, purchase, and sell goods and services. However, this sector faces a myriad of challenges that impede its sustainable growth and development. This research paper critically examines the current problems encountered by the electronic commerce sector and proposes viable solutions to address these issues. The study identifies three major problem areas affecting the sector: (1) Security and Privacy Concerns, (2) Logistics and Supply Chain Bottlenecks, and (3) Customer Experience and Trust. Regarding security and privacy, the proliferation of cyber-attacks, data breaches, and identity theft has eroded consumer confidence, hindering e-commerce adoption. The paper aims to investigate the latest technologies and best practices, such as blockchain, advanced encryption techniques, and robust authentication methods, to fortify e-commerce platforms against cyber threats and safeguard user data. The second problem area, logistics and supply chain bottleneck, poses challenges related to order fulfilment, inventory management, and last-mile delivery. Through an in-depth analysis, the research proposes innovative approaches like utilizing machine learning algorithms for predictive inventory management, integrating Internet of Things (IoT) devices for real-time tracking, and exploring drone and autonomous vehicle deliveries to enhance overall logistics efficiency. The third issue addressed in this paper pertains to customer experience and trust. The inability to tangibly experience products before purchase, coupled with ambiguous return policies, often deters potential customers from engaging in e-commerce transactions. The study delves into augmented reality (AR) and virtual reality (VR) applications to simulate product experiences and advocates for transparent and customer centric return policies. This research paper sheds li

关键词： Supply chains

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