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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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Augmented reality-based visual-haptic modeling for thoracoscopic surgery training systems

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virtual reality & Intelligent Hardware 2021年第4期3卷 274-286页

作者： Yonghang TAI Junsheng SHI Junjun PAN Aimin HAO Victor CHANG Yunnan Key Lab Optoelectronic Information Technology Yunnan Normal UniversityKunming 650500China State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191China School of Computing Engineering and Digital TechnologiesTeesside UniversityMiddlesbrough TS13BXUK

Background Compared with traditional thoracotomy,video-assisted thoracoscopic surgery(VATS)has less minor trauma,faster recovery,higher patient compliance,but higher requirements for *** surgery training simulation systems are important and have been widely used in Europe and *** reality(AR)in surgical training simulation systems significantly improve the training effect of virtual surgical training,although AR technology is still in its initial *** reality has gained increased attention in technology-driven modern medicine but has yet to be used in everyday *** This study proposed an immersive AR lobectomy within a thoracoscope surgery training system,using visual and haptic modeling to study the potential benefits of this critical *** content included immersive AR visual rendering,based on the cluster-based extended position-based dynamics algorithm of soft tissue physical ***,we designed an AR haptic rendering systems,whose model architecture consisted of multi-touch interaction points,including kinesthetic and pressure-sensitive ***,based on the above theoretical research,we developed an AR interactive VATS surgical training *** Twenty-four volunteers were recruited from the First People's Hospital of Yunnan Province to evaluate the VATS training ***,content,and construct validation methods were used to assess the tactile sense,visual sense,scene authenticity,and simulator *** The results of our construction validation demonstrate that the simulator is useful in improving novice and surgical skills that can be retained after a certain period of *** video-assisted thoracoscopic system based on AR developed in this study is effective and can be used as a training device to assist in the development of thoracoscopic skills for novices.

关键词： Augmented reality VATS Surgery training XPBD

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The Approach of Equipment Degradation Processes Considering Self-Recovery Characteristics

The Approach of Equipment Degradation Processes Considering ...

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International Conference on Reliability, Maintainability and Safety,ICRMS

作者： Weixuan Zhou Chuan Lv Jie Geng Yuxue Jin Miao Zhang Zhuoying Gao School of Reliability and Systems Engineering Beihang University Beijing China State key laboratory of virtual reality technology and system Beihang University Beijing China Key laboratory of reliability and environmental engineering Beihang University Beijing China

ISBN: (数字)9798350329988

ISBN: (纸本)9798350329995

Recent research in the process of equipment state evolution emphasizes the comprehensive consideration of the event process. However, the process does not consider the self-recovery capability of equipment in detail. In view of this problem, a detailed explanation of the self-recovery characteristics is given. Subsequently, a self-recovery model for equipment is established. Furthermore, the degradation process considering self-recovery is established. Finally, a numerical analysis is carried out to give the degradation process curve with self-recovery characteristics. The result shows that the degradation process can reflect the state evolution process more comprehensively for the equipment with self-recovery capability.

关键词： Degradation Numerical analysis Safety Numerical models Reliability

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Evaluation of Vibrotactile Glove and Handheld Controller in a Visuo-Haptic VR Space Station

Evaluation of Vibrotactile Glove and Handheld Controller in ...

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Automation, Robotics and Computer Engineering (ICARCE), International Conference on

作者： Hu Luo Zejian Zhou Tianyang Cao Yufeng Na Jingwen Nie Ruixue Bai Dangxiao Wang State Key Lab of Virtual Reality Technology and System Beihang University Beijing China Beijing SpaceD Aerospace Application & Science Education Co. Ltd. Beijing China School of General Engineering Beihang University Beijing China

Using virtual reality technology, we can simulate the microgravity environment of the outer space for popularizing the space science. Compared with handheld controllers, we expect using a glove with localized vibrotactile feedback might be more efficient and natural for simulating grasping gestures for space roaming and 3D-objects manipulating, however, quantitative and qualitative effects remain unknown. Thus, this study developed a science popularization orientated visuo-haptic VR space station for elucidating the difference between the two interaction devices. We used the number of times of trying to grasp, success grasping rate, and total time of completing the roaming task to objectively describe the interacting efficiency. The results of subjective rating showed better motion intuitiveness and vibrotactile fidelity using the vibrotactile glove, however, quantitative results showed using the glove was less efficient as compared to using the handheld controller. So, analyses of the underlying reasons were performed in aspects of both hardware and software. The findings may provide suggestions for designing VR interacting devices for space science popularization.

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QR-CLIP: Introducing Explicit Open-World Knowledge for Location and Time Reasoning

arXiv

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arXiv 2023年

作者： Shi, Weimin Zhuge, Mingchen Gao, Dehong Zhou, Zhong Cheng, Ming-Ming Fan, Deng-Ping State Key Laboratory of Virtual Reality Technology and System Beihang University Beijing China Saudi Arabia Northwestern Polytechnical University Xian China The Nankai University Tianjin China ETH Zurich Zurich Switzerland

Daily images can convey abstract meanings that require us to memorize and infer profound information. To encourage human-like reasoning, in this work, we teach machines to predict where and when the image was captured. Inspired by Hutchins’s theory of Distributed Cognition, we design a new model called QR-CLIP, which is composed of two components. 1) The Quantity Module expands cognitive resources by accumulating as much open-world knowledge as possible from the environment, thereby enhancing cognitive ability. 2) The Relevance Module integrates relevant information from various cognitive tools to create a comprehensive cognitive outcome. Experiments have shown the effectiveness of our QR-CLIP, which outperforms the previous SOTA methods on each task, achieving an average relative improvement of ∼10% and ∼110% in terms of location and time reasoning, respectively. This study provides a technical foundation for location and time reasoning and suggests that effectively interacting with open-world knowledge is one of the solutions for the tasks. The source code is available at https://***/Shi-Wm/QR-CLIP. Copyright © 2023, The Authors. All rights reserved.

关键词： Location

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A Comprehensive Survey of Action Quality Assessment: Method and Benchmark

arXiv

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arXiv 2024年

作者： Zhou, Kanglei Cai, Ruizhi Wang, Liyuan Shum, Hubert P.H. Liang, Xiaohui State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China The Department of Computer Science and Technology Institute for AI BNRist Center THBI Lab Tsinghua-Bosch Joint Center for ML Tsinghua University Beijing100190 China The Department of Computer Science Durham University DurhamDH1 3LE United Kingdom The State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China Zhongguancun Laboratory Beijing China

Action Quality Assessment (AQA) quantitatively evaluates the quality of human actions, providing automated assessments that reduce biases in human judgment. Its applications span domains such as sports analysis, skill assessment, and medical care. Recent advances in AQA have introduced innovative methodologies, but similar methods often intertwine across different domains, highlighting the fragmented nature that hinders systematic reviews. In addition, the lack of a unified benchmark and limited computational comparisons hinder consistent evaluation and fair assessment of AQA approaches. In this work, we address these gaps by systematically analyzing over 150 AQA-related papers to develop a hierarchical taxonomy, construct a unified benchmark, and provide an in-depth analysis of current trends, challenges, and future directions. Our hierarchical taxonomy categorizes AQA methods based on input modalities (video, skeleton, multi-modal) and their specific characteristics, highlighting the evolution and interrelations across various approaches. To promote standardization, we present a unified benchmark, integrating diverse datasets to evaluate the assessment precision and computational efficiency. Finally, we review emerging task-specific applications and identify under-explored challenges in AQA, providing actionable insights into future research directions. This survey aims to deepen understanding of AQA progress, facilitate method comparison, and guide future innovations. The project web page can be found at https://***/AQA-Survey. Copyright © 2024, The Authors. All rights reserved.

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Reading Chinese in Natural Scenes with a Bag-of-Radicals Prior

arXiv

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arXiv 2022年

作者： Liu, Ongbin Liu, Ingjie Chen, Iaxin Wang, Unhong School of Computer Science and Engineering Beihang University Beijing China State Key Laboratory of Virtual Reality Technology System Beihang University Beijing China

Scene text recognition (STR) on Latin datasets has been extensively studied in recent years, and state-of-the-art (SOTA) models often reach high accuracy. However, the performance on non-Latin transcripts, such as Chinese, is not satisfactory. In this paper, we collect six open-source Chinese STR datasets and evaluate a series of classic methods performing well on Latin datasets, finding a significant performance drop. To improve the performance on Chinese datasets, we propose a novel radical-embedding (RE) representation to utilize the ideographic descriptions of Chinese characters. The ideographic descriptions of Chinese characters are firstly converted to bags of radicals and then fused with learnable character embeddings by a character-vector-fusion-module (CVFM). In addition, we utilize a bag of radicals as supervision signals for multi-task training to improve the ideographic structure perception of our model. Experiments show performance of the model with RE + CVFM + multi-task training is superior compared with the baseline on six Chinese STR datasets. Copyright © 2022, The Authors. All rights reserved.

关键词： Embeddings

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Intelligent recognition of portrait sketch components for child autism assessment

Intelligent recognition of portrait sketch components for ch...

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作者： Shen, Yang Wang, Xinyu Chen, Zhangmeng Sun, Qi Zhang, Xu Liang, Hui Pan, Junjun Collaborative Innovation Center of Assessment for Basic Education Quality Beijing Normal University Beijing China State Key Laboratory of Virtual Reality Technology & Systems Beihang University Beijing China Peng Cheng Lab Shenzhen China Zhengzhou University of Light Industry Zhengzhou China

For autistic children with slow language function, it is a classic and easy way to understand the development of their cognitive ability through simple painting experiments. Due to the lack of professional evaluators for painting assessment of autistic children, this article research and implement an intelligent assessment system for child autism through recognition of portrait sketch components. A portrait sketch database is constructed with the sample size of 30,400 after data expansion. The data consists of two formats: stroke vector sequence and 2D image. Then we propose a joint model coupled with LSTM and CNN features to automatically segment the portrait sketch components. It can perform better segmentation for exaggerated proportion and incomplete components samples. Finally, according to the evaluation criteria of the painting, we design an assessment model for child autism. The experiments are conducted in cooperation with relevant rehabilitation institutions to verify the effectiveness of the system. The analysis results show that our painting assessment system has a good ability to identify autistic tendencies. It can accurately evaluate children's autistic tendencies through "draw-a-man" experiments. © 2022 John Wiley & Sons, Ltd.

关键词： Diseases

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3D reconstruction from endoscopy images: A survey

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Computers in Biology and Medicine 2024年 175卷 108546-108546页

作者： Yang, Zhuoyue Dai, Ju Pan, Junjun State Key Laboratory of Virtual Reality Technology and Systems Beihang University 37 Xueyuan Road Haidian District Beijing100191 China Peng Cheng Lab 2 Xingke 1st Street Nanshan District ShenzhenGuangdong Province518000 China

Three-dimensional reconstruction of images acquired through endoscopes is playing a vital role in an increasing number of medical applications. Endoscopes used in the clinic are commonly classified as monocular endoscopes and binocular endoscopes. We have reviewed the classification of methods for depth estimation according to the type of endoscope. Basically, depth estimation relies on feature matching of images and multi-view geometry theory. However, these traditional techniques have many problems in the endoscopic environment. With the increasing development of deep learning techniques, there is a growing number of works based on learning methods to address challenges such as inconsistent illumination and texture sparsity. We have reviewed over 170 papers published in the 10 years from 2013 to 2023. The commonly used public datasets and performance metrics are summarized. We also give a taxonomy of methods and analyze the advantages and drawbacks of algorithms. Summary tables and result atlas are listed to facilitate the comparison of qualitative and quantitative performance of different methods in each category. In addition, we summarize commonly used scene representation methods in endoscopy and speculate on the prospects of deep estimation research in medical applications. We also compare the robustness performance, processing time, and scene representation of the methods to facilitate doctors and researchers in selecting appropriate methods based on surgical applications. © 2024 Elsevier Ltd

关键词： Endoscopy

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Few-shot fine-grained action recognition via bidirectional attention and contrastive meta-learning

arXiv

引用

arXiv 2021年

作者： Wang, Jiahao Wang, Yunhong Liu, Sheng Li, Annan State Key Laboratory of Virtual Reality Technology and System Beihang University Beijing China

Fine-grained action recognition is attracting increasing attention due to the emerging demand of specific action understanding in real-world applications, whereas the data of rare fine-grained categories is very limited. Therefore, we propose the few-shot finegrained action recognition problem, aiming to recognize novel fine-grained actions with only few samples given for each class. Although progress has been made in coarse-grained actions, existing few-shot recognition methods encounter two issues handling finegrained actions: the inability to capture subtle action details and the inadequacy in learning from data with low inter-class variance. To tackle the first issue, a human vision inspired bidirectional attention module (BAM) is proposed. Combining top-down task-driven signals with bottom-up salient stimuli, BAM captures subtle action details by accurately highlighting informative spatio-temporal regions. To address the second issue, we introduce contrastive metalearning (CML). Compared with the widely adopted ProtoNet-based method, CML generates more discriminative video representations for low inter-class variance data, since it makes full use of potential contrastive pairs in each training episode. Furthermore, to fairly compare different models, we establish specific benchmark protocols on two large-scale fine-grained action recognition datasets. Extensive experiments show that our method consistently achieves state-of-the-art performance across evaluated tasks. Copyright © 2021, The Authors. All rights reserved.

关键词： Large dataset

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