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436 results on '"Wu, Zhongke"'

1. Consistent Point Orientation for Manifold Surfaces via Boundary Integration

Author

Liu, Weizhou, Wang, Xingce, Zhao, Haichuan, Xue, Xingfei, Wu, Zhongke, Lu, Xuequan, and He, Ying

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Graphics
Abstract

This paper introduces a new approach for generating globally consistent normals for point clouds sampled from manifold surfaces. Given that the generalized winding number (GWN) field generated by a point cloud with globally consistent normals is a solution to a PDE with jump boundary conditions and possesses harmonic properties, and the Dirichlet energy of the GWN field can be defined as an integral over the boundary surface, we formulate a boundary energy derived from the Dirichlet energy of the GWN. Taking as input a point cloud with randomly oriented normals, we optimize this energy to restore the global harmonicity of the GWN field, thereby recovering the globally consistent normals. Experiments show that our method outperforms state-of-the-art approaches, exhibiting enhanced robustness to noise, outliers, complex topologies, and thin structures. Our code can be found at \url{https://github.com/liuweizhou319/BIM}., Comment: accepted in siggraph2024

Published
2024

2. Diffusing Winding Gradients (DWG): A Parallel and Scalable Method for 3D Reconstruction from Unoriented Point Clouds

Author

Liu, Weizhou, Li, Jiaze, Chen, Xuhui, Hou, Fei, Xin, Shiqing, Wang, Xingce, Wu, Zhongke, Qian, Chen, and He, Ying

Subjects
Computer Science - Graphics
Abstract

This paper presents a method for reconstructing watertight 3D surfaces from unoriented point clouds. Starting with randomly initialized normals, the method iteratively refines each normal by diffusing the gradient of the generalized winding number (GWN) field. Upon convergence, the target surface is extracted using the standard Marching Cubes algorithm. Our method is conceptually simple, easy to implement, and does not require numerical solvers, which distinguishes it from existing approaches. Designed for parallelization and scalability, it efficiently handles large-scale models on both CPUs and GPUs. Experimental results demonstrate that our method outperforms all existing methods in reconstructing from unoriented point clouds, particularly in terms of runtime performance. On large-scale models with 10 to 20 million points, our CUDA implementation on an NVIDIA GTX 4090 GPU is typically 30-100x faster than iPSR, the leading sequential method tested on a high-end PC with an Intel i9 CPU. Furthermore, our approach exhibits superior robustness against noise and effectively handles models with thin structures, surpassing existing methods. We will make the source code publicly available to encourage further research and applications.

Published
2024

3. Enhancing Sign Language Teaching: A Mixed Reality Approach for Immersive Learning and Multi-Dimensional Feedback

Author

Wen, Hongli, Xu, Yang, Li, Lin, Ru, Xudong, Wang, Xingce, and Wu, Zhongke

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Traditional sign language teaching methods face challenges such as limited feedback and diverse learning scenarios. Although 2D resources lack real-time feedback, classroom teaching is constrained by a scarcity of teacher. Methods based on VR and AR have relatively primitive interaction feedback mechanisms. This study proposes an innovative teaching model that uses real-time monocular vision and mixed reality technology. First, we introduce an improved hand-posture reconstruction method to achieve sign language semantic retention and real-time feedback. Second, a ternary system evaluation algorithm is proposed for a comprehensive assessment, maintaining good consistency with experts in sign language. Furthermore, we use mixed reality technology to construct a scenario-based 3D sign language classroom and explore the user experience of scenario teaching. Overall, this paper presents a novel teaching method that provides an immersive learning experience, advanced posture reconstruction, and precise feedback, achieving positive feedback on user experience and learning effectiveness., Comment: 8 pages, 6 figures

Published
2024

5. Dynamic Ball B-Spline Curves

Author

Zhou, Ciyang, Zhang, Yu, Wang, Xingce, Wu, Zhongke, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Sheng, Bin, editor, Bi, Lei, editor, Kim, Jinman, editor, Magnenat-Thalmann, Nadia, editor, and Thalmann, Daniel, editor

Published
2024
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10. The Architecture of an Automatic eHealth Platform With Mobile Client for Cerebrovascular Disease Detection

Author

Wang, Xingce, Bie, Rongfang, Sun, Yunchuan, Wu, Zhongke, Zhou, Mingquan, Cao, Rongfei, Xie, Lizhi, and Zhang, Dong

Subjects
Information technology, T58.5-58.64, Public aspects of medicine, RA1-1270
Abstract

BackgroundIn recent years, cerebrovascular disease has been the leading cause of death and adult disability in the world. This study describes an efficient approach to detect cerebrovascular disease. ObjectiveIn order to improve cerebrovascular treatment, prevention, and care, an automatic cerebrovascular disease detection eHealth platform is designed and studied. MethodsWe designed an automatic eHealth platform for cerebrovascular disease detection with a four-level architecture: object control layer, data transmission layer, service supporting layer, and application service layer. The platform has eight main functions: cerebrovascular database management, preprocessing of cerebral image data, image viewing and adjustment model, image cropping compression and measurement, cerebrovascular segmentation, 3-dimensional cerebrovascular reconstruction, cerebrovascular rendering, cerebrovascular virtual endoscope, and automatic detection. Several key technologies were employed for the implementation of the platform. The anisotropic diffusion model was used to reduce the noise. Statistics segmentation with Gaussian-Markov random field model (G-MRF) and Stochastic Estimation Maximization (SEM) parameter estimation method were used to realize the cerebrovascular segmentation. Ball B-Spline curve was proposed to model the cerebral blood vessels. Compute unified device architecture (CUDA) based on ray-casting volume rendering presented by curvature enhancement and boundary enhancement were used to realize the volume rendering model. We implemented the platform with a network client and mobile phone client to fit different users. ResultsThe implemented platform is running on a common personal computer. Experiments on 32 patients’ brain computed tomography data or brain magnetic resonance imaging data stored in the system verified the feasibility and validity of each model we proposed. The platform is partly used in the cranial nerve surgery of the First Hospital Affiliated to the General Hospital of People's Liberation Army and radiology of Beijing Navy General Hospital. At the same time it also gets some applications in medical imaging specialty teaching of Tianjin Medical University. The application results have also been validated by our neurosurgeon and radiologist. ConclusionsThe platform appears beneficial in diagnosis of the cerebrovascular disease. The long-term benefits and additional applications of this technology warrant further study. The research built a diagnosis and treatment platform of the human tissue with complex geometry and topology such as brain vessel based on the Internet of things.

Published
2013
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21. Harnessing Cloud Computing to Power Up HPC Applications: The BRICS CloudHPC Project

Author

Marques, Jonatas A., Wu, Zhongke, Wang, Xingce, Kuchumov, Ruslan, Korkhov, Vladimir, Cordeiro, Weverton L. C., Navaux, Philippe O. A., Gaspary, Luciano P., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Gervasi, Osvaldo, editor, Murgante, Beniamino, editor, Misra, Sanjay, editor, Garau, Chiara, editor, Blečić, Ivan, editor, Taniar, David, editor, Apduhan, Bernady O., editor, Rocha, Ana Maria A. C., editor, Tarantino, Eufemia, editor, and Torre, Carmelo Maria, editor

Published
2021
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22. GLS‐PIA: n‐Dimensional Spherical B‐Spline Curve Fitting based on Geodesic Least Square with Adaptive Knot Placement.

Author

Zhao, Yuming, Wu, Zhongke, and Wang, Xingce

Subjects
CURVE fitting, GEODESICS, POINT set theory, SQUARE, SPHERES, PARAMETRIC equations
Abstract

Due to the widespread applications of curves on n‐dimensional spheres, fitting curves on n‐dimensional spheres has received increasing attention in recent years. However, due to the non‐Euclidean nature of spheres, curve fitting methods on n‐dimensional spheres often struggle to balance fitting accuracy and curve fairness. In this paper, we propose a new fitting framework, GLS‐PIA, for parameterized point sets on n‐dimensional spheres to address the challenge. Meanwhile, we provide the proof of the method. Firstly, we propose a progressive iterative approximation method based on geodesic least squares which can directly optimize the geodesic least squares loss on the n‐sphere, improving the accuracy of the fitting. Additionally, we use an error allocation method based on contribution coefficients to ensure the fairness of the fitting curve. Secondly, we propose an adaptive knot placement method based on geodesic difference to estimate a more reasonable distribution of control points in the parameter domain, placing more control points in areas with greater detail. This enables B‐spline curves to capture more details with a limited number of control points. Experimental results demonstrate that our framework achieves outstanding performance, especially in handling imbalanced data points. (In this paper, "sphere" refers to n‐sphere (n ≥ 2) unless otherwise specified.) [ABSTRACT FROM AUTHOR]

Published
2024
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23. Aneurysm Identification in Cerebral Models with Multiview Convolutional Neural Network

Author

Zhou, Mingsong, Wang, Xingce, Wu, Zhongke, Pozo, Jose M., Frangi, Alejandro F., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Crimi, Alessandro, editor, and Bakas, Spyridon, editor

Published
2020
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31. A Scale Normalization Algorithm Based on MR-GDS for Archaeological Fragments Reassembly

Author

Yin, Congli, Zhou, Pengbo, Zhou, Mingquan, Wu, Zhongke, Du, Guoguang, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Zhao, Yao, editor, Barnes, Nick, editor, Chen, Baoquan, editor, Westermann, Rüdiger, editor, Kong, Xiangwei, editor, and Lin, Chunyu, editor

Published
2019
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32. Intracranial Aneurysm Detection from 3D Vascular Mesh Models with Ensemble Deep Learning

Author

Zhou, Mingsong, Wang, Xingce, Wu, Zhongke, Pozo, Jose M., Frangi, Alejandro F., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Shen, Dinggang, editor, Liu, Tianming, editor, Peters, Terry M., editor, Staib, Lawrence H., editor, Essert, Caroline, editor, Zhou, Sean, editor, Yap, Pew-Thian, editor, and Khan, Ali, editor

Published
2019
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33. Boosting HPC Applications in the Cloud Through JIT Traffic-Aware Path Provisioning

Author

Pretto, Guilherme R., Dalmazo, Bruno L., Marques, Jonatas A., Wu, Zhongke, Wang, Xingce, Korkhov, Vladimir, Navaux, Philippe O. A., Gaspary, Luciano P., Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Misra, Sanjay, editor, Gervasi, Osvaldo, editor, Murgante, Beniamino, editor, Stankova, Elena, editor, Korkhov, Vladimir, editor, Torre, Carmelo, editor, Rocha, Ana Maria A.C., editor, Taniar, David, editor, Apduhan, Bernady O., editor, and Tarantino, Eufemia, editor

Published
2019
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34. Mixed-Model Noise Removal in 3D MRI via Rotation-and-Scale Invariant Non-Local Means

Author

Liu, Xiangyuan, Liu, Quansheng, Wu, Zhongke, Wang, Xingce, Pozo Sole, Jose, Frangi, Alejandro, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Lepore, Natasha, editor, Brieva, Jorge, editor, Romero, Eduardo, editor, Racoceanu, Daniel, editor, and Joskowicz, Leo, editor

Published
2019
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43. Automatic Labeling of Vascular Structures with Topological Constraints via HMM

Author

Wang, Xingce, Liu, Yue, Wu, Zhongke, Mou, Xiao, Zhou, Mingquan, Ballester, Miguel A. González, Zhang, Chong, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Descoteaux, Maxime, editor, Maier-Hein, Lena, editor, Franz, Alfred, editor, Jannin, Pierre, editor, Collins, D. Louis, editor, and Duchesne, Simon, editor

Published
2017
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