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Monocular Video Guided Garment Simulation

Journal of computer Science & technology 2015年第3期30卷 528-539页

作者：李发明陈小武周彬卢飞翔郭侃符强 State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing 100191 China

We present a prototype to generate a garment-shape sequence guided by a monocular video sequence. It is a combination of a physically-based simulation and a boundary-based modification. Given a garment in the video worn on a mannequin, the simulation generates a garment initial shape by exploiting the mannequin shapes estimated from the video. The modification then deforms the simulated 3D shape into such a shape that matches the garment 2D boundary extracted from the video. According to the matching correspondences between the vertices on the shape and the points on the boundary, the modification is implemented by attracting the matched vertices and their neighboring vertices. For best-matching correspondences and efficient performance, three criteria are introduced to select the candidate vertices for matching. Since modifying each garment shape independently may cause inter-frame oscillations, changes by the modification are also propagated from one frame to the next frame. As a result, the generated garment 3D shape sequence is stable and similar to the garment video sequence. We demonstrate the effectiveness of our prototype with a number of examples.

关键词： garment simulation monocular video shape correspondence

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Multiplane-based Cross-view Interaction Mechanism for Robust Light Field Angular Super-Resolution

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IEEE Transactions on Visualization and computer Graphics 2025年 PP卷 PP页

作者： Chen, Rongshan Sheng, Hao Yang, Da Cong, Ruixuan Cui, Zhenglong Wang, Sizhe Ke, Wei Beihang University Data Science and Intelligent Computing Laboratory Hangzhou International Innovation Institute Zhejiang Hangzhou311115 China Beihang University State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beijing100191 China Macao Polytechnic University Faculty of Applied Sciences 999078 China Macao Polytechnic University School of Applied Sciences 999078 China

Dense sampling of the light field (LF) is essential for various applications, such as virtual reality. However, the collection process is prohibitively expensive due to technological limitations in imaging. Synthesizing novel views from sparse LF data, known as LF Angular Super-Resolution (LFASR), offers an effective solution to this problem. Accurate cross-view interaction is crucial for this task, given the complementary information between LF views. Previous methods, however, suffer from limited reconstruction quality due to inefficient view interaction. To address this, we propose a Multiplane-based Cross-view Interaction Mechanism (MCIM) for robust LFASR. Extensive comparisons with state-of-the-art methods demonstrate that our method achieves superior performance, both visually and quantitatively. Specifically, Drawing inspiration from MultiPlane Images (MPI) in scene modeling, our mechanism incorporates a novel Multiplane Feature Fusion (MPFF) strategy. This strategy facilitates fast and accurate cross-view interaction, enhancing the network's robustness to scene geometry and suitability for different-baseline LF scenes. Furthermore, to address information redundancy in multiplanes, we leverage the transparency property of MPI and devise a plane selection strategy. Finally, we propose CSTNet, a Cross-Shaped Transformer-based network for LFASR, which employs a cross-shaped self-attention mechanism to enable low-cost training and inference. Experimental results on various angular super-resolution tasks validate that our network achieves state-of-the-art performance on both synthetic and real-world LF scenes. © 1995-2012 IEEE.

关键词： virtual reality

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Ore genesis and critical metal enrichment using deep learning algorithms in Gunga Pb-Zn deposit, Southern Pakistan: Constraints from sphalerite geochemistry and isotopic compositions

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Journal of Geochemical Exploration 2025年 275卷

作者： Gul, Muhammad A. Zhang, Huishan Yang, Yu Ren, Guangli Sun, Chao Zhao, Xiaojian Yousuf, Tahir Bin Shah, Ahmed Awan, Rizwan Sarwar Faisal, Mohamed Yang, Xiaoyong CAS Key Laboratory of Crust-Mantle Materials and Environments University of Science and Technology of China Hefei230026 China CAS Center for Excellence in Comparative Planetology University of Science and Technology of China Hefei230026 China MNR Key Laboratory for the Study of Focused Magmatism and Giant Ore Deposits Xi'an Center of Geological Survey CGS Xi'an710054 China Department of Computer Science and IT Virtual University Lahore Pakistan Center of Excellence in Mineralogy University of Baluchistan Quetta Pakistan School of Environment and Resources Engineering Hefei University of Technology Hefei China Department of Geology Faculty of Science Suez Canal University El-Ismailia41522 Egypt School of Geosciences and Info-Physics Central South University Changsha410083 China

The Kirthar Fold and Thrust Belt in southern Pakistan is widely recognized as a major metallogenic province owing to the extensive presence of Pb-Zn deposits within the Jurassic sedimentary shelf sequence. One of these deposits, the Gunga Pb-Zn deposit, is a significant economic ore deposit situated within the Anjira Formation and comprises two mineralization zones, the Upper Mineralization Zone (UMZ) and Lower Mineralization Zone (LMZ). Despite the scarcity of documentation on the metallogenic source, origin, mineralization temperature, and other physicochemical conditions, our research is the first to explore the metallogenic differentiation and ore genesis of the deposit by examining minor and trace elements in sphalerite and isotopic analyses (S-Pb). The Gunga Pb-Zn deposit, amounting to 6.86 Mt. with 2.1 % and 11.4 % Pb and Zn, respectively, is linked to the interbedded limestone and shale unit of the Anjira Formation, and approximately below the depth of 200–250 m of the Jurassic-Cretaceous contact, the mineralization is believed to occur in the upper section of the Formation. Sphalerite is the dominant ore mineral, galena is a subordinate mineral, and pyrite is present in the main ore minerals. Sphalerite in the LMZ was found in a vein style, whereas it was disseminated in the UMZ and enriched in (medians) Ge (166 ppm), Cd (541 ppm), Pb (139 ppm), Ag (42 ppm), and Hg (68 ppm), lacking In (0.17 ppm), Co (6 ppm), and Mn (19). Based on trace element concentrations, the LMZ has a reduced environment, higher sulfur fugacity, and higher mineralization temperature (180–200 °C) than the UMZ, which has a lower mineralization temperature (130–180 °C). The presence of black shales, low temperatures, and high sulfur fugacity are the key parameters for Ge enrichment in the Gunga deposit. The δ34S values range from −10 to +5.6 ‰, suggesting that reduced sulfur was produced by both the BSR and TSR mechanisms, with basinal brines and seawater being the main sources of sulfur

关键词： Sulfur

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3D Dental Model Segmentation with Geometrical Boundary Preserving

arXiv

引用

arXiv 2025年

作者： Xi, Shufan Liu, Zexian Chang, Junlin Wu, Hongyu Wang, Xiaogang Hao, Aimin State Key Laboratory of Virtual Reality Technology and Systems Beihang University China College of Computer and Information Science Southwest University China Peng Cheng Laboratory China

3D intraoral scan mesh is widely used in digital dentistry diagnosis, segmenting 3D intraoral scan mesh is a critical preliminary task. Numerous approaches have been devised for precise tooth segmentation. Currently, the deep learning-based methods are capable of the high accuracy segmentation of crown. However, the segmentation accuracy at the junction between the crown and the gum is still below average. Existing down-sampling methods are unable to effectively preserve the geometric details at the junction. To address these problems, we propose CrossTooth, a boundary-preserving segmentation method that combines 3D mesh selective downsampling to retain more vertices at the tooth-gingiva area, along with cross-modal discriminative boundary features extracted from multi-view rendered images, enhancing the geometric representation of the segmentation network. Using a point network as a backbone and incorporating image complementary features, CrossTooth significantly improves segmentation accuracy, as demonstrated by experiments on a public intraoral scan dataset. The source code is available at https://***/XiShuFan/CrossTooth_CVPR2025 Copyright © 2025, The Authors. All rights reserved.

关键词： Image segmentation

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Depression Scale Dictionary Decomposition Framework for Multimodal Automatic Depression Level Prediction

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IEEE Transactions on Circuits and Systems for Video technology 2025年

作者： Niu, Mingyue Wang, Xu Gong, Jibing Liu, Bin Tao, Jianhua Schuller, Bjorn W. Yanshan University School of Information Science and Engineering Hebei province Qinhuangdao066004 China Hebei Key Laboratory of Computer Virtual Technology and System Integration China Technology Co. Ltd Bejing100022 China Bejing100190 China Tsinghua University Department of Automation Bejing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China University of Augsburg ZD.B. Chair of Embedded Intelligence for Health Care and Wellbeing Augsburg Germany Glam - Group on Language Audio and Music United Kingdom

Currently, many researchers aim to achieve automatic depression level prediction via speech and video behavior analysis. However, previous works have struggled to decompose audio and video sequences into the information related to and unrelated to depression scores, hindering the model's perception of depression cues. Besides, previous works implement multimodal fusion using attention mechanisms or linear layers, but failed to simultaneously consider the Euclidean relationship among tokens and the non-Euclidean relationship among channels, which bring limitations in capturing depression cues. In response to the above issues, we propose a depression scale dictionary decomposition framework, which mainly includes a Bidirectional Dictionary Decomposition (BDD) module and a Bidirectional Multimodal Fusion (BMF) module. The BDD module can use the dictionaries generated based on the depression scale to semantically decompose audio and video sequences into the information related to and unrelated to depression scores along token and channel dimensions for promoting depression cue perception. Moreover, considering the respective characteristics of tokens and channels, the BMF module uses linear layers and graph convolution to achieve cross-modal mixing, which is used to aggregate audio and video sequences for predicting depression levels. The validation on AVEC 2013, AVEC 2014 and DAIC-WOZ datasets demonstrates our method's superiority. © 1991-2012 IEEE.

关键词： Boolean functions

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Fast and compact dynamic data compression based on composite rigid body construction

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Science China(Information Sciences) 2014年第11期57卷 66-84页

作者： MA ZhiQiang WANG LiLi ZHANG BoNing KE Wei ZHAO QinPing State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang University Macao Polytechnic Institute

3D dynamic datasets compression still poses two challenges. One is high time cost due to growing data and complex computation of compression algorithms. The other is low compression factor because of complex motions of dynamic scenes and unknown motion equations. In this paper, composite rigid body construction for fast and compact compression of 3D dynamic datasets is proposed to solve these two problems. It accelerates the compression with a fast rigid body decomposition based on disjoint union, and avoids serial searching, comparing and merging of the rigid body decomposition. To increase the compression factor,composite rigid body is introduced with consideration of motion consistency among rigid bodies at different time periods. The results of the experiments show that our algorithm compresses dynamic datasets quickly and achieves a high compression factor.

关键词： time-varying datasets dynamic datasets compression rigid body decomposition disjoint union composite rigid body construction

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A CADe system for nodule detection in thoracic CT images based on artificial neural network

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Science China(Information Sciences) 2017年第7期60卷 177-194页

作者： Xinglong LIU Fei HOU Hong QIN Aimin HAO State Key Laboratory of Virtual Reality Technology and Systems Beihang University School of Computer Science and Engineering Nanyang Technological University Department of Computer Science Stony Brook University

Lung cancer has been the leading cause of cancer-related deaths in 2015 in United States. Early detection of lung nodules will undoubtedly increase the five-year survival rate for lung cancer according to prior studies. In this paper, we propose a novel rating method based on geometrical and statistical features to extract initial nodule candidates and an artificial neural network approach to the detection of lung nodules. The novel method is solely based on 3D distribution of neighboring voxels instead of user-specified features. During initial candidates detection, we combine organized region properties calculated from connected component analysis with corresponding voxel value distributions from statistical analysis to reduce false positives while retaining true nodules. Then we devise multiple artificial neural networks(ANNs) trained from massive voxel neighbor sampling of different types of nodules and organize the outputs using a 3D scoring method to identify final nodules. The experiments on 107 CT cases with 252 nodules in LIDC-IDRI data sets have shown that our new method achieves sensitivity of 89.4% while reducing the false positives to 2.0 per case. Our comprehensive experiments have demonstrated our system would be of great assistance for diagnosis of lung nodules in clinical treatments.

关键词： artificial neutral network Lung nodule computed tomography computer aided detection nodule detection

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A point-based rendering approach for real-time interaction on mobile devices

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Science in China(Series F) 2009年第8期52卷 1335-1345页

作者： LIANG XiaoHui ZHAO QinPing HE ZhiYing XIE Ke LIU YuBo State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Technology Beihang UniversityBeijing 100191 China

Mobile device is an important interactive platform. Due to the limitation of computation, memory, display area and energy, how to realize the efficient and real-time interaction of 3D models based on mobile devices is an important research topic. Considering features of mobile devices, this paper adopts remote rendering mode and point models, and then, proposes a transmission and rendering approach that could interact in real time. First, improved simplification algorithm based on MLS and display resolution of mobile devices is proposed. Then, a hierarchy selection of point models and a QoS transmission control strategy are given based on interest area of operator, interest degree of object in the virtual environment and rendering error. They can save the energy consumption. Finally, the rendering and interaction of point models are completed on mobile devices. The experiments show that our method is efficient.

关键词： virtual environment mobile devices point models simplification QoS control area of interest interest degree

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A Novel Nonlinear Parameter Estimation Method of Soft Tissues

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Genomics, Proteomics & Bioinformatics 2017年第6期15卷 371-380页

作者： Qianqian Tong Zhiyong Yuan Mianlun Zheng Xiangyun Liao Weixu Zhu Guian Zhang School of Computer Wuhan University Shenzhen Key Laboratory of Virtual Reality and Human Interaction Technology Shenzhen Institutes of Advanced TechnologyChinese Academy of Sciences

The elastic parameters of soft tissues are important for medical diagnosis and virtual surgery simulation. In this study, we propose a novel nonlinear parameter estimation method for soft tissues. Firstly, an in-house data acquisition platform was used to obtain external forces and their corresponding deformation values, To provide highly precise data for estimating nonlinear param- eters, the measured forces were corrected using the constructed weighted combination forecasting model based on a support vector machine （WCFM_SVM）. Secondly, a tetrahedral finite element parameter estimation model was established to describe the physical characteristics of soft tissues, using the substitution parameters of Young＇s modulus and Poisson＇s ratio to avoid solving compli- cated nonlinear problems. To improve the robustness of our model and avoid poor local minima, the initial parameters solved by a linear finite element model were introduced into the parameter estimation model. Finally, a self-adapting Levenberg-Marquardt （LM） algorithm was presented, which is capable of adaptively adjusting iterative parameters to solve the established parameter estimation model. The maximum absolute error of our WCFM SVM model was less than 0.03 Newton, resulting in more accurate forces in comparison with other correction models tested. The maximum absolute error between the calculated and measured nodal displacements was less than 1.5 mm, demonstrating that our nonlinear parameters are precise.

关键词： Nonlinear parameter estimation Finite element method Substitution parameters Force correction Self-adapting Levenberg-Marquardt algorithm

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Toward Lung Ultrasound Automation: Fully Autonomous Robotic Longitudinal and Transverse Scans Along Intercostal Spaces

IEEE Transactions on Medical Robotics and Bionics

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IEEE Transactions on Medical Robotics and Bionics 2025年第2期7卷 768-781页

作者： Long Lei Yingbai Hu Zixing Jiang Juzheng Miao Xiao Luo Yu Zhang Qiong Wang Shujun Wang Zheng Li Pheng-Ann Heng Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Multi-Scale Medical Robotics Centre Ltd. The Chinese University of Hong Kong Hong Kong China Department of Surgery The Chinese University of Hong Kong Hong Kong China Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Department of Biomedical Engineering The Hong Kong Polytechnic University Hong Kong China Department of Surgery Chow Yuk Ho Technology Centre for Innovative Medicine Li Ka Shing Institute of Health Sciences and Multiscale Medical Robotics Centre Ltd. The Chinese University of Hong Kong Hong Kong China

Lung ultrasound scanning is essential for diagnosing lung diseases. The scan effectiveness critically depends on both longitudinal and transverse scans through intercostal spaces to reduce rib shadowing interference, as well as maintaining the probe perpendicular to pleura for pathological artifact generation. Achieving this level of scan quality often depends heavily on the experience of doctors. Robotic ultrasound scanning shows promise, but currently lacks a direct path planning method for intercostal scanning, and probe orientation does not consider imaging differences between lungs and solid organs. In this paper, we aim to fully automate two fundamental operations in lung ultrasound scanning: longitudinal and transverse scans. We propose pioneering path planning methods along intercostal spaces and innovative solutions for adaptive probe posture adjustment using real-time pleural line feedback, specifically addressing the unique characteristics of lung ultrasound scanning. This ensures the acquisition of high-quality, diagnostically meaningful ultrasound images. In addition, we develop a robotic lung ultrasound system to validate the proposed methods. Extensive experimental results on two volunteers and a chest phantom confirm the efficacy of our methods, and demonstrate the system’s feasibility in automated lung ultrasound examinations. Our work lays a solid foundation for automated robotic complete lung scanning.

关键词： Ultrasonic imaging Lungs Probes Robots Robot kinematics Medical robotics Ribs Medical services Surface morphology Computed tomography

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