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9th International Symposium on Artificial Intelligence and Robotics, ISAIR 2024

作者： Zhang, Tianrui Wang, Aizeng School of Mechanical Engineering and Automation Beihang University Beijing100191 China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing100191 China

ISBN: (纸本)9789819629138

This paper introduces an improved neural network that integrates residual network and attention mechanisms, achieving a significant improvement of 99.50% accuracy in mechanical part classification tasks. The proposed network enhance accuracy, precision, recall, and F1-score compared to traditional CNNs and other advanced networks in handling complex backgrounds and multi-angle part images. This advancement shows potential in smart manufacturing, offering greater automation, minimizing human intervention. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Smart manufacturing

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Research on Object Oriented Plan Management System modeling

Research on Object Oriented Plan Management System modeling

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Junjun Chang Chao Yang Jin Xiao Southwest China Research Institute of Electronic Equipment Chengdu China The State Key Lab of Virtual Reality Technology and Systems Beihang University Beijing China

Under the background that the manufacturing industry is facing the digital transformation, the demand for business modeling is increasingly urgent. Only through business modeling can business processes, business rules and the authority and boundary of roles be sorted out, so as to solve the problem of "information island" among the information systems of various departments of the enterprise. There are many modeling languages/tools that can be applied to business modeling at home and abroad, including flowchart, Event-driven Process Chain(EPC), ICAM Definition Languages(IDEF), Business Process Model and Notation(BPMN) and Unified Modeling Language(UML), etc. Each of these languages/tools has its own advantages and disadvantages. Business modeling under the background of digital transformation is not limited to the traditional "description" of business processes and business rules, but more to find a modeling method, starting from the needs of the organization, step by step to "develop" a business system in line with the expectations of the organization; However, at present, the academic and industrial research on this aspect is very little. Inspired by the history of software development methodology shifting from a process-oriented to an object-oriented method, this paper considers business modeling based on UML and object-oriented method. There are many object-oriented modeling methods. Through research, we find that HarmonySE method can be applied to business modeling to meet the needs of business modeling under the background of digital transformation. Then, it details how to model a plan management system based on UML and HarmonySE methodologies on Astah Professional, a UML modeling tool. Finally, the advantages of business modeling based on UML and HarmonySE are described.

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Facilitating Asymmetric Interaction between VR Users and External Users via Wearable Gesture-Based Interface

Facilitating Asymmetric Interaction between VR Users and Ext...

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virtual reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Yuetong Zhao Shuo Yan Xuanmiao Zhang Xukun Shen School of New Media Art and Design Beihang University State Key Laboratory of Virtual Reality Technology and Systems Beihang University

Head-mounted displays (HMDs) create a highly immersive experience, while limit VR users' awareness of external users that co-located in the same environment. Previous studies generate various asymmetric communication that allowing external users to collaborate with VR users. In our work, we designed a wearable gesture-based interface for external users in two main asymmetric VR scenarios: (1) Object Transition and (2) Collaborative Game. We conducted a hybrid user study with twenty participants to compare the gesture-based interaction and controller-based interaction to investigate the effects on VR experience, social presence, and collaborative efficiency for external users. Our study revealed that the participants in gesture-based interaction received more positive feedbacks compared to those in controller-based interaction. Our findings suggested that the gesture-based interaction could be adapted for future asymmetric VR experience.

关键词： Three-dimensional displays Head-mounted displays Costs Conferences Collaboration Immersive experience Games

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Glass Wool Defect Detection Using an Improved YOLOv5

Glass Wool Defect Detection Using an Improved YOLOv5

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IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Yizhou Jin Yu Lu Gang Zhou Qingjie Liu Yunhong Wang State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China Hangzhou Innovation Institute Beihang University

Glass wool defect detection is a key part of product quality assessment in the glass wool production process, yet few studies have been reported in this area. We propose a glass wool defect dataset named GWD, and also use the YOLOv5s model embedded in the GSConv and the CBAM modules for both Gap and Glueless defects in this dataset. The experimental results show that the performance of the improved YOLOv5s on the GWD dataset is superior to other compared methods and achieves a relatively good level on other publicly available datasets. Compared to the vanilla YOLOv5s, the mAP50 increased by 3.7% to 84.1%, the recall increased by 4.2% to 84.4%, and the number of parameters decreased by 0.42 MB to 6.27 MB of the improved YOLOv5s model on the GWD dataset. Speed-wisely, the improved YOLOv5s achieves a 97 FPS on RTX 2080Ti, thus making it practical to be applied in the industry of glass wool defect detection. The research on the GWD dataset is likely to contribute to breakthroughs in research on other datasets of the same type as well. The GWD dataset can be obtained by contacting us via email.

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A Solution to Co-occurrence Bias: Attributes Disentanglement via Mutual Information Minimization for Pedestrian Attribute Recognition

arXiv

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arXiv 2023年

作者： Zhou, Yibo Hu, Hai-Miao Yu, Jinzuo Xu, Zhenbo Lu, Weiqing Cao, Yuran State key laboratory of virtual reality technology and systems Beihang University China Hangzhou Innovation Institute Beihang University China

Recent studies on pedestrian attribute recognition progress with either explicit or implicit modeling of the co-occurrence among attributes. Considering that this known a prior is highly variable and unforeseeable regarding the specific scenarios, we show that current methods can actually suffer in generalizing such fitted attributes interdependencies onto scenes or identities off the dataset distribution, resulting in the underlined bias of attributes co-occurrence. To render models robust in realistic scenes, we propose the attributes-disentangled feature learning to ensure the recognition of an attribute not inferring on the existence of others, and which is sequentially formulated as a problem of mutual information minimization. Rooting from it, practical strategies are devised to efficiently decouple attributes, which substantially improve the baseline and establish state-of-the-art performance on realistic datasets like PETAzs and RAPzs. © 2023, CC BY.

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A Comparison of Gesture-based Interaction and Controller-based Interaction for External Users in Co-located Asymmetric virtual reality

A Comparison of Gesture-based Interaction and Controller-bas...

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virtual reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Yuetong Zhao Shuo Yan Xuanmiao Zhang Xukun Shen School of New Media Art and Design Beihang University State Key Laboratory of Virtual Reality Technology and Systems Beihang University

Head-mounted displays (HMDs) create a highly immersive experience, while limit VR users' awareness of external users that co-located in the same environment. In our work, we designed a wearable gesture-based interface for external users in two main asymmetric VR scenarios: (1) Object Transition, (2) Collaborative Game. We conducted a hybrid user study with twenty participants to compare the gesture-based interaction and controller-based interaction to investigate the effects on VR experience, social presence, and collaborative efficiency for external users. Our study revealed that the participants in gesture-based interaction received more positive feedback compared to those in controller-based interaction.

关键词： Three-dimensional displays Head-mounted displays Costs Conferences Collaboration Immersive experience Games

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Odometry with Real-Time Depth Completion for UAV Location in Denied Environment

Odometry with Real-Time Depth Completion for UAV Location in...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Jin Xiao Zhangchenyu Liu Xiaoguang Hu Zichong Jia Weipeng Wang State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China Beihang University Beijing China The Third Academy of CASIC Beijing China

ISBN: (数字)9798350360868

ISBN: (纸本)9798350360875

With the advent of the information age, the application of unmanned aerial vehicles (UAVs) has become increasingly frequent, and the combat scenarios have become more diverse. How to enable UAVs to achieve precise localization in a denial environment has become a focal point of interest. Consequently, Simultaneous Localization and Mapping (SLAM) technology is widely used on UAVs. Within SLAM technology, depth information provides a critical guarantee for precise localization. Depth completion, as an important issue in computer vision, leverages sparse depth data obtained from sensors and combines it with semantic information provided by color images to acquire dense depth information of the scene. Following this idea, this paper improves a multimodal fusion SLAM algorithm and integrating an improved depth completion algorithm to enhance the localization accuracy of the SLAM system and expand its mapping ability.

关键词： Location awareness Point cloud compression Simultaneous localization and mapping Laser radar Semantics Autonomous aerial vehicles Information age

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MvEchoSeg: One-shot In-context Learning for Multi-view Echocardiography Segmentation

MvEchoSeg: One-shot In-context Learning for Multi-view Echoc...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Guo, Yuting Duan, Ya Song, Wenfeng Li, Nannan Li, Aili Li, Shuai Beihang University State Key Laboratory of Virtual Reality Technology and Systems Beijing100191 China University of Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Beijing Information Science and Technology University School of Computer Science Beijing100192 China Dalian Maritime University School of Information Science and Technology Dalian116000 China China-Japan Friendship Hospital Beijing100029 China

ISBN: (纸本)9798350386226

Echocardiography is the clinical standard for evaluation of cardiac morphology, and function, and providing hemodynamic parameters in patients with known or suspected heart disease. Due to the diversity and complexity of diagnostic tasks, comprehensive interpretation of echocardiography often requires multi-view imaging for integrated metric analysis. Deep learning methods have become the mainstream approach for echocardiography segmentation. However, achieving segmentation of multi-view echocardiography still requires a substantial amount of annotation. To remedy this, we propose a one-shot in-context learning network mvEchoSeg for multi-view echocardiography segmentation. This network requires only one annotated image for each view. Specifically, we propose a Task Prompt Identifier (TPI) module to identify the task type of the image and allocate the most precise task prompt for it, with minimal adaptation of CLIP and few-shot strategies. Additionally, we leverage a unified In-Context Model (ICM) capable of performing a diverse set of echocardiography segmentation tasks automatically. Using fine-tuning and low-rank adapters improved the performance of the pre-trained model, achieving significant results with minimal training cost. Furthermore, we collect a multi-view echocardiography dataset (MVECD) with 8 views to evaluate our method. The results show an improvement of more than 10% in the DICE score compared to the SOTA foundational medical image segmentation models. To our knowledge, this is the first exploration of a one-shot model for multi-view echocardiography segmentation. Our codes and models are available at https://***/stellating/mvEchoSeg. © 2024 IEEE.

关键词： Image segmentation

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Locomotion perception and redirection

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virtual reality & Intelligent Hardware 2021年第6期3卷 I0003-I0004页

作者： Miao WANG Songhai ZHANG Shimin HU State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China

Locomotion is a fundamental interaction technique that allows free navigation in virtual scenes.A large body of literature has demonstrated that natural locomotion experience can significantly improve the sense of presence and help users achieve better performance in tasks such as searching and *** the upcoming metaverse era,locomotion will play a critical role in the success of large-scale interactive *** and redirection are two tightly connected problems in virtual *** a limited physical condition and a target virtual scene,how to make the perceived locomotion as natural as possible,and further unknowingly redirect the user in the physical world is an open *** this special issue,we have selected five papers that provide their latest updates for research problems of view control,virtual jumping,climbing,and searching.

关键词： redirect interactive motion

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Heterogeneous Mixture of Experts for Remote Sensing Image Super-Resolution

arXiv

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arXiv 2025年

作者： Chen, Bowen Chen, keyan Yang, Mohan Zou, Zhengxia Shi, Zhenwei Department of Aerospace Intelligent Science and Technology School of Astronautics Beihang University Beijing100191 China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing100191 China

Remote sensing image super-resolution (SR) aims to reconstruct high-resolution remote sensing images from low-resolution inputs, thereby addressing limitations imposed by sensors and imaging conditions. However, the inherent characteristics of remote sensing images, including diverse ground object types and complex details, pose significant challenges to achieving high-quality reconstruction. Existing methods typically employ a uniform structure to process various types of ground objects without distinction, making it difficult to adapt to the complex characteristics of remote sensing images. To address this issue, we introduce a Mixture of Experts (MoE) model and design a set of heterogeneous experts. These experts are organized into multiple expert groups, where experts within each group are homogeneous while being heterogeneous across groups. This design ensures that specialized activation parameters can be employed to handle the diverse and intricate details of ground objects effectively. To better accommodate the heterogeneous experts, we propose a multi-level feature aggregation strategy to guide the routing process. Additionally, we develop a dual-routing mechanism to adaptively select the optimal expert for each pixel. Experiments conducted on the UCMerced and AID datasets demonstrate that our proposed method achieves superior SR reconstruction accuracy compared to state-of-the-art methods. The code will be available at https://***/Mr-Bamboo/MFG-HMoE. Copyright © 2025, The Authors. All rights reserved.

关键词： Optical resolving power

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