检索结果-内蒙古大学图书馆

A novel local/global approach to spherical parameterization

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2018年 329卷 294-306页

作者： Wang, Zhao Luo, Zhongxuan Zhang, Jielin Saucan, Emil Dalian Univ Technol Sch Math Sci Dalian Peoples R China Dalian Univ Technol Sch Software Dalian Peoples R China North China Univ Sci & Technol Coll Sci Tangshan Peoples R China Jilin Univ Sch Math Changchun Jilin Peoples R China Max Planck Inst Math Sci Leipzig Germany

This paper proposes a novel local global spherical parameterization for the genus-zero triangular mesh, which naturally extends the planar approach to the spherical case. In our method, we derive two fitting matrices (conformal and isometric) in 3D space. By optimizing the so-called spring energy, the spherical results are achieved by solving a nonlinear system with spherical constraints. Intuitively, it represents the stitching together of the 1-ring patches to form a unit sphere. Moreover, the derivation of the 3D fitting matrices can also be applied to planar triangles directly, so that we can obtain a class of novel planar approaches (conformal, isometric, authalic) to the problem of flattening triangular meshes. In order to enhance robustness of the proposed spherical method, a stretch operator is introduced for dealing with high-curvature models. Numerical results demonstrate that our method is simple, efficient and convergent, and it outperforms several state-of-the-art methods in terms of trading-off the distortions of angle, area and stretch. Furthermore, it achieves better visualization in texture mapping. (C) 2017 Published by Elsevier B.V.

关键词： Geometric modeling spherical parameterization Stretch operator

来源：评论

学校读者我要写书评

暂无评论

spherical parameterization Balancing Angle and Area Distortions

引用

IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2017年第6期23卷 1663-1676页

作者： Nadeem, Saad Su, Zhengyu Zeng, Wei Kaufman, Arie Gu, Xianfeng SUNY Stony Brook Comp Sci Dept Stony Brook NY 11794 USA Florida Int Univ Sch Comp & Informat Sci Miami FL USA

This work presents a novel framework for spherical mesh parameterization. An efficient angle-preserving spherical parameterization algorithm is introduced, which is based on dynamic Yamabe flow and the conformal welding method with solid theoretic foundation. An area-preserving spherical parameterization is also discussed, which is based on discrete optimal mass transport theory. Furthermore, a spherical parameterization algorithm, which is based on the polar decomposition method, balancing angle distortion and area distortion is presented. The algorithms are tested on 3D geometric data and the experiments demonstrate the efficiency and efficacy of the proposed methods.

关键词： spherical parameterization conformal map area-preserving map ricci flow optimal mass transport

来源：评论

学校读者我要写书评

暂无评论

A Study on the Influence of Wavelet Number Change in the Wavelet Neural Network Architecture for 3D Mesh Deformation Using Trust Region spherical parameterization 27th

A Study on the Influence of Wavelet Number Change in the Wav...

引用

27th International Conference on Artificial Neural Networks (ICANN)

作者： Dhibi, Naziha Elkefai, Akram Ben Amar, Chokri Univ Sfax ENIS REGIM Lab Sfax Tunisia

ISBN: (纸本)9783030014216

The 3D deformation and simulation process frequently include much iteration of geometric design changes. We propose in this paper a study on the influence of wavelet number change in the wavelet neural network architecture for 3D mesh deformation method. Our approach is focused on creating the series of intermediate objects to have the target object, using trust region spherical parameterization algorithm as a common domain of the source and target objects that minimizing angle and area distortions which assurance bijective 3D spherical parameterization, and we used a multi-library wavelet neural network structure (MLWNN) as an approximation tools for feature alignment between the source and the target models to guarantee a successful deformation process. Experimental results show that the spherical parameterization algorithm preserves angle and area distortion, a MLWNN structure relying on various mother wavelets families (MLWNN) to align mesh features and minimize distortion with fixed features, and the increasing of wavelets number makes it possible to facilitate the features alignment which implies the reduction of the error between the objects thus reducing the rate of deformation to have good deformation scheme.

关键词： 3D mesh deformation spherical parameterization Trust region algorithm Wavelet neural network

来源：评论

学校读者我要写书评

暂无评论

Multivariate GARCH models with spherical parameterizations: an oil price application

引用

FINANCIAL INNOVATION 2025年第1期11卷 1-20页

作者： Ballestra, Luca Vincenzo De Blasis, Riccardo Pacelli, Graziella Alma Mater Studiorum Univ Bologna Dept Stat Sci Paolo Fortunati Bologna Italy Marche Polytech Univ Dept Management Ancona Italy

In popular Baba-Engle-Kraft-Kroner (BEKK) and dynamic conditional correlation (DCC) multivariate generalized autoregressive conditional heteroskedasticity models, the large number of parameters and the requirement of positive definiteness of the covariance and correlation matrices pose some difficulties during the estimation process. To avoid these issues, we propose two modifications to the BEKK and DCC models that employ two spherical parameterizations applied to the Cholesky decompositions of the covariance and correlation matrices. In their full specifications, the introduced Cholesky-BEKK and Cholesky-DCC models allow for a reduction in the number of parameters compared with their traditional counterparts. Moreover, the application of spherical transformation does not require the imposition of inequality constraints on the parameters during the estimation. An application to two crude oils, WTI and Brent, and the main exchange rate prices demonstrates that the Cholesky-BEKK and Cholesky-DCC models can capture the dynamics of covariances and correlations. In addition, the Kupiec test on different portfolio compositions confirms the satisfactory performance of the proposed models.

关键词： BEKK Cholesky-GARCH Crude oils DCC Exchange rates spherical parameterization

来源：评论

学校读者我要写书评

暂无评论

Evaluation of spherical parameterization Methods for Three-dimensional Reconstruction of Medical images

Evaluation of Spherical Parameterization Methods for Three-d...

引用

2nd International Conference on Machine Design and Manufacturing Engineering (ICMDME)

作者： Wu, Xing Hui Hao, Zhi Xiu Tsinghua Univ State Key Lab Tribol Div Intelligent & Biomech Syst Beijing 100084 Peoples R China

ISBN: (纸本)9783037857816

The spherical parameterization is important for the correspondence problem that is a major part of statistical shape modelling for the reconstruction of patient-specific 3D models from medical images. In this paper, we present comparative studies of five common spherical mapping methods applied to the femur and tibia models: the Issenburg et al. method, the Alexa method, the Saba et al. method, the Praun et al. method and the Shen et al. method. These methods are evaluated using three sets of measures: distortion property, geometric error and distance to standard landmarks. Results show that the Praun et al. method performs better than other methods while the Shen et al. method can be regarded as the most reliable one for providing an acceptable correspondence result. We suggest that the area preserving property can be used as a sufficient condition while the angle preserving property is not important when choosing a spherical mapping method for correspondence application.

关键词： spherical parameterization correspondence problem statistical shape modelling three dimensional reconstruction image visualization

来源：评论

学校读者我要写书评

暂无评论

Single image-based head pose estimation with spherical parametrization and 3D morphing

引用

PATTERN RECOGNITION 2020年 103卷 107316-107316页

作者： Yuan, Hui Li, Mengyu Hou, Junhui Xiao, Jimin Shandong Univ Sch Control Sci & Engn Jinan Peoples R China Shandong Univ Sch Informat Sci & Engn Jinan Peoples R China City Univ Hong Kong Dept Comp Sci Kowloon Hong Kong Peoples R China Xian Jiaotong Liverpool Univ Dept Elect & Elect Engn Suzhou Peoples R China

Head pose estimation plays a vital role in various applications, e.g., driver-assistance systems, human-computer interaction, virtual reality technology, and so on. We propose a novel geometry-based method for accurately estimating the head pose from a single 2D face image at a very low computational cost. Specifically, the rectangular coordinates of only four non-coplanar feature points from a predefined 3D facial model as well as the corresponding ones automatically/manually extracted from a 2D face image are first normalized to exclude the effect of external factors (i.e., scale factor and translation parameters). Then, the four normalized 3D feature points are represented in spherical coordinates with reference to the uniquely determined sphere by themselves. Due to the spherical parametrization, the coordinates of feature points can then be morphed along all the three directions in the rectangular coordinates effectively. Finally, the rotation matrix indicating the head pose is obtained by minimizing the Euclidean distance between the normalized 2D feature points and the 2D re-projections of the morphed 3D feature points. Comprehensive experimental results over two popular datasets, i.e., Pointing'04 and Biwi Kinect, demonstrate that the proposed method can estimate head poses with higher accuracy and lower run time than state-of-the-art geometry-based methods. Even compared with start-of-the-art learning-based methods or geometry-based methods with additional depth information, our method still produces comparable performance. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Head pose estimation spherical parameterization 3D facial model

来源：评论

学校读者我要写书评

暂无评论

spherical Orbifold Tutte Embeddings

引用

ACM TRANSACTIONS ON GRAPHICS 2017年第4期36卷 1-13页

作者： Aigerman, Noam Kovalsky, Shahar Z. Lipman, Yaron Weizmann Inst Sci Rehovot Israel Duke Univ Durham NC 27706 USA

This work presents an algorithm for injectively parameterizing surfaces into spherical target domains called spherical orbifolds. spherical orbifolds are cone surfaces that are generated from symmetry groups of the sphere. The surface is mapped the spherical orbifold via an extension of Tutte's embedding. This embedding is proven to be bijective under mild additional assumptions, which hold in all experiments performed. This work also completes the adaptation of Tutte's embedding to orbifolds of the three classic geometries - Euclidean, hyperbolic and spherical - where the first two were recently addressed. The spherical orbifold embeddings approximate conformal maps and require relatively low computational times. The constant positive curvature of the spherical orbifolds, along with the flexibility of their cone angles, enables producing embeddings with lower isometric distortion compared to their Euclidean counterparts, a fact that makes spherical orbifolds a natural candidate for surface parameterization.

关键词： spherical parameterization orbifolds Tutte's embedding

来源：评论

学校读者我要写书评

暂无评论

Semi-regular Remeshing based trust region spherical geometry image for 3D deformed mesh used MLWNN 9

Semi-regular Remeshing based trust region spherical geometry...

引用

9th International Conference on Machine Vision (ICMV)

作者： Dhibi, Naziha Elkefi, Akram Bellil, Wajdi Ben amar, Chokri Univ Sfax REGIM Natl Engn Sch Sfax Sfax Tunisia

ISBN: (纸本)9781510611320

Triangular surface are now widely used for modeling three-dimensional object, since these models are very high resolution and the geometry of the mesh is often very dense, it is then necessary to remesh this object to reduce their complexity, the mesh quality (connectivity regularity) must be ameliorated. In this paper, we review the main methods of semi-regular remeshing of the state of the art, given the semi-regular remeshing is mainly relevant for wavelet-based compression, then we present our method for re-meshing based trust region spherical geometry image to have good scheme of 3d mesh compression used to deform 3D meh based on Multi library Wavelet Neural Network structure (MLWNN). Experimental results show that the progressive re-meshing algorithm capable of obtaining more compact representations and semi-regular objects and yield an efficient compression capabilities with minimal set of features used to have good 3D deformation scheme.

关键词： Remeshing spherical parameterization Geometry image Compression 3D deformation

来源：评论

学校读者我要写书评

暂无评论

Direct method for rotation estimation from spherical images using 3D mesh surfaces with SPHARM representation

引用

JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2016年第PartB期40卷 708-720页

作者： Benseddik, Houssem-Eddine Hadj-Abdelkader, Hicham Cherki, Brahim Bouchafa, Samia Univ Evry Lab IBISC Evry France Univ Tlemcen Lab Automat Tilimsen Algeria Ctr Dev Technol Avancees Algiers Algeria

Since a large field of view obviously bears important advantages, the use of spherical images is becoming increasingly important in various computer vision and image processing applications. This paper presents a novel rotation estimation approach for spherical images based on 3D mesh representation of gray level intensity. Once the 3D meshes of the underlying spherical images are obtained, the 3D rotation can be estimated directly and efficiently, without feature extraction and matching process. Subsequently, we propose a direct method for 3D object rotation estimation using spherical harmonics representation with SVD decomposition and ICP algorithm for estimation refinement. Experimental results validate our approach and prove its suitability and robustness for rotation estimation. Moreover, it performs well against noisy images, brightness changes, image compression and occlusions. A comparative study of our proposed approach with four similar methods for 3D rotation estimation between spherical images, is realized to prove its effectiveness. (C) 2016 Elsevier Inc. All rights reserved.

关键词： Rotation estimation 3D mesh surfaces spherical images spherical harmonic functions spherical parameterization 3D mesh generation

来源：评论

学校读者我要写书评

暂无评论

3D High Resolution Mesh Deformation Based on Multi Library Wavelet Neural Network Architecture

引用

3D RESEARCH 2016年第4期7卷 1-14页

作者： Dhibi, Naziha Elkefi, Akram Bellil, Wajdi Ben Amar, Chokri Univ Sfax Natl Sch Engineers ENIS REGIM Res Grp Intelligent Machines Sfax 3038 Tunisia

This paper deals with the features of a novel technique for large Laplacian boundary deformations using estimated rotations. The proposed method is based on a Multi Library Wavelet Neural Network structure founded on several mother wavelet families (MLWNN). The objective is to align features of mesh and minimize distortion with a fixed feature that minimizes the sum of the distances between all corresponding vertices. New mesh deformation method worked in the domain of Region of Interest (ROI). Our approach computes deformed ROI, updates and optimizes it to align features of mesh based on MLWNN and spherical parameterization configuration. This structure has the advantage of constructing the network by several mother wavelets to solve high dimensions problem using the best wavelet mother that models the signal better. The simulation test achieved the robustness and speed considerations when developing deformation methodologies. The Mean-Square Error and the ratio of deformation are low compared to other works from the state of the art. Our approach minimizes distortions with fixed features to have a well reconstructed object.

关键词： Deformations spherical parameterization Correspondence Wavelet Neural Network 3D high resolution meshes

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：