Pub Date : 2024-04-24DOI: 10.1016/j.cagd.2024.102309
Yang Zhou , Cheng Xu , Zhiqiang Lin , Xinwei He , Hui Huang
A point cloud is a set of discrete surface samples. As the simplest 3D representation, it is widely used in 3D reconstruction and perception. Yet developing a generative model for point clouds remains challenging due to the sparsity and irregularity of points. Drawn by StyleGAN, the forefront image generation model, this paper presents Point-StyleGAN, a generator adapted from StyleGAN2 architecture for point cloud synthesis. Specifically, we replace all the 2D convolutions with 1D ones and introduce a series of multi-resolution discriminators to overcome the under-constrained issue caused by the sparsity of points. We further add a metric learning-based loss to improve generation diversity. Besides the generation task, we show several applications based on GAN inversion, among which an inversion encoder Point-pSp is designed and applied to point cloud reconstruction, completion, and interpolation. To our best knowledge, Point-pSp is the first inversion encoder for point cloud embedding in the latent space of GANs. The comparisons to prior work and the applications of GAN inversion demonstrate the advantages of our method. We believe the potential brought by the Point-StyleGAN architecture would further inspire massive follow-up works.
点云是一组离散的表面样本。作为最简单的三维表示,它被广泛应用于三维重建和感知。然而,由于点的稀疏性和不规则性,为点云开发生成模型仍然具有挑战性。本文借鉴最前沿的图像生成模型 StyleGAN,提出了点云生成模型 Point-StyleGAN,这是一种从 StyleGAN2 架构改编而来的点云合成生成器。具体来说,我们用一维卷积替换了所有二维卷积,并引入了一系列多分辨率判别器,以克服由点稀疏性导致的约束不足问题。我们还进一步添加了基于度量学习的损失,以提高生成多样性。除了生成任务,我们还展示了基于 GAN 反演的几种应用,其中设计了一种反演编码器 Point-pSp,并将其应用于点云重建、补全和插值。据我们所知,Point-pSp 是第一个用于在 GAN 潜在空间中嵌入点云的反转编码器。与之前工作的比较以及 GAN 反演的应用证明了我们方法的优势。我们相信,Point-StyleGAN 架构所带来的潜力将进一步激发大量后续工作。
{"title":"Point-StyleGAN: Multi-scale point cloud synthesis with style modulation","authors":"Yang Zhou , Cheng Xu , Zhiqiang Lin , Xinwei He , Hui Huang","doi":"10.1016/j.cagd.2024.102309","DOIUrl":"https://doi.org/10.1016/j.cagd.2024.102309","url":null,"abstract":"<div><p>A point cloud is a set of discrete surface samples. As the simplest 3D representation, it is widely used in 3D reconstruction and perception. Yet developing a generative model for point clouds remains challenging due to the sparsity and irregularity of points. Drawn by StyleGAN, the forefront image generation model, this paper presents Point-StyleGAN, a generator adapted from StyleGAN2 architecture for point cloud synthesis. Specifically, we replace all the 2D convolutions with 1D ones and introduce a series of multi-resolution discriminators to overcome the under-constrained issue caused by the sparsity of points. We further add a metric learning-based loss to improve generation diversity. Besides the generation task, we show several applications based on GAN inversion, among which an inversion encoder Point-pSp is designed and applied to point cloud reconstruction, completion, and interpolation. To our best knowledge, Point-pSp is the first inversion encoder for point cloud embedding in the latent space of GANs. The comparisons to prior work and the applications of GAN inversion demonstrate the advantages of our method. We believe the potential brought by the Point-StyleGAN architecture would further inspire massive follow-up works.</p></div>","PeriodicalId":55226,"journal":{"name":"Computer Aided Geometric Design","volume":"111 ","pages":"Article 102309"},"PeriodicalIF":1.5,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140645563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-24DOI: 10.1016/j.cagd.2024.102320
Yiheng Lv , Guangshun Wei , Yeying Fan , Long Ma , Dongxu Liu , Yuanfeng Zhou
The aesthetic appeal and removability of clear aligners have led to their widespread popularity in orthodontic treatments. Dental attachments significantly contribute to shortening treatment duration and enhancing orthodontic outcomes. The automation of tailor-made dental attachments for individual teeth plays a crucial role in the field of orthodontics. This is because they enable more precise control over the forces applied, thereby effectively facilitating tooth movement. This study introduces an automated algorithm that generates dental attachments based on the orthodontic path. The algorithm automatically selects and places the appropriate type of attachment according to the magnitude of rotation and translation of teeth during orthodontic procedures. It adjusts the position and posture of the attachments to fit the teeth accurately. To validate the effectiveness of automatically placed attachments in guiding teeth along the predetermined path, this study employs finite element analysis to simulate the impact of attachments on teeth. Comparative analyses between the automated method and traditional manual techniques show that the proposed algorithm significantly enhances the precision and efficiency of attachment placement. Additionally, finite element simulations confirm the feasibility and effectiveness of this approach in clinical orthodontic applications, providing a novel technical pathway for automating attachment placement in orthodontic treatments and offering significant practical value for personalized and efficient orthodontic care.
{"title":"Automated placement of dental attachments based on orthodontic pathways","authors":"Yiheng Lv , Guangshun Wei , Yeying Fan , Long Ma , Dongxu Liu , Yuanfeng Zhou","doi":"10.1016/j.cagd.2024.102320","DOIUrl":"https://doi.org/10.1016/j.cagd.2024.102320","url":null,"abstract":"<div><p>The aesthetic appeal and removability of clear aligners have led to their widespread popularity in orthodontic treatments. Dental attachments significantly contribute to shortening treatment duration and enhancing orthodontic outcomes. The automation of tailor-made dental attachments for individual teeth plays a crucial role in the field of orthodontics. This is because they enable more precise control over the forces applied, thereby effectively facilitating tooth movement. This study introduces an automated algorithm that generates dental attachments based on the orthodontic path. The algorithm automatically selects and places the appropriate type of attachment according to the magnitude of rotation and translation of teeth during orthodontic procedures. It adjusts the position and posture of the attachments to fit the teeth accurately. To validate the effectiveness of automatically placed attachments in guiding teeth along the predetermined path, this study employs finite element analysis to simulate the impact of attachments on teeth. Comparative analyses between the automated method and traditional manual techniques show that the proposed algorithm significantly enhances the precision and efficiency of attachment placement. Additionally, finite element simulations confirm the feasibility and effectiveness of this approach in clinical orthodontic applications, providing a novel technical pathway for automating attachment placement in orthodontic treatments and offering significant practical value for personalized and efficient orthodontic care.</p></div>","PeriodicalId":55226,"journal":{"name":"Computer Aided Geometric Design","volume":"111 ","pages":"Article 102320"},"PeriodicalIF":1.5,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140649955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mesh denoising is a crucial research topic in geometric processing, as it is widely used in reverse engineering and 3D modeling. The main objective of denoising is to eliminate noise while preserving sharp features. In this paper, we propose a novel denoising method called Attention Enhanced Dual Mesh Denoise (ADMD), which is based on a graph neural network and attention mechanism. ADMD simulates the two-stage denoising method by using a new training strategy and total variation (TV) regular term to enhance feature retention. Our experiments have demonstrated that ADMD can achieve competitive or superior results to state-of-the-art methods for noise CAD models, non-CAD models, and real-scanned data. Moreover, our method can effectively handle large mesh models with different-scale noisy situations and prevent model shrinking after mesh denoising.
{"title":"An attention enhanced dual graph neural network for mesh denoising","authors":"Mengxing Wang , Yi-Fei Feng , Bowen Lyu , Li-Yong Shen , Chun-Ming Yuan","doi":"10.1016/j.cagd.2024.102307","DOIUrl":"https://doi.org/10.1016/j.cagd.2024.102307","url":null,"abstract":"<div><p>Mesh denoising is a crucial research topic in geometric processing, as it is widely used in reverse engineering and 3D modeling. The main objective of denoising is to eliminate noise while preserving sharp features. In this paper, we propose a novel denoising method called Attention Enhanced Dual Mesh Denoise (ADMD), which is based on a graph neural network and attention mechanism. ADMD simulates the two-stage denoising method by using a new training strategy and total variation (TV) regular term to enhance feature retention. Our experiments have demonstrated that ADMD can achieve competitive or superior results to state-of-the-art methods for noise CAD models, non-CAD models, and real-scanned data. Moreover, our method can effectively handle large mesh models with different-scale noisy situations and prevent model shrinking after mesh denoising.</p></div>","PeriodicalId":55226,"journal":{"name":"Computer Aided Geometric Design","volume":"111 ","pages":"Article 102307"},"PeriodicalIF":1.5,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140645560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-24DOI: 10.1016/j.cagd.2024.102304
Qiujie Dong , Xiaoran Gong , Rui Xu , Zixiong Wang , Junjie Gao , Shuangmin Chen , Shiqing Xin , Changhe Tu , Wenping Wang
Given the rapid advancements in geometric deep-learning techniques, there has been a dedicated effort to create mesh-based convolutional operators that act as a link between irregular mesh structures and widely adopted backbone networks. Despite the numerous advantages of Convolutional Neural Networks (CNNs) over Multi-Layer Perceptrons (MLPs), mesh-oriented CNNs often require intricate network architectures to tackle irregularities of a triangular mesh. These architectures not only demand that the mesh be manifold and watertight but also impose constraints on the abundance of training samples. In this paper, we note that for specific tasks such as mesh classification and semantic part segmentation, large-scale shape features play a pivotal role. This is in contrast to the realm of shape correspondence, where a comprehensive understanding of 3D shapes necessitates considering both local and global characteristics. Inspired by this key observation, we introduce a task-driven neural network architecture that seamlessly operates in an end-to-end fashion. Our method takes as input mesh vertices equipped with the heat kernel signature (HKS) and dihedral angles between adjacent faces. Notably, we replace the conventional convolutional module, commonly found in ResNet architectures, with MLPs and incorporate Layer Normalization (LN) to facilitate layer-wise normalization. Our approach, with a seemingly straightforward network architecture, demonstrates an accuracy advantage. It exhibits a marginal 0.1% improvement in the mesh classification task and a substantial 1.8% enhancement in the mesh part segmentation task compared to state-of-the-art methodologies. Moreover, as the number of training samples decreases to 1/50 or even 1/100, the accuracy advantage of our approach becomes more pronounced. In summary, our convolution-free network is tailored for specific tasks relying on large-scale shape features and excels in the situation with a limited number of training samples, setting itself apart from state-of-the-art methodologies.
{"title":"A task-driven network for mesh classification and semantic part segmentation","authors":"Qiujie Dong , Xiaoran Gong , Rui Xu , Zixiong Wang , Junjie Gao , Shuangmin Chen , Shiqing Xin , Changhe Tu , Wenping Wang","doi":"10.1016/j.cagd.2024.102304","DOIUrl":"https://doi.org/10.1016/j.cagd.2024.102304","url":null,"abstract":"<div><p>Given the rapid advancements in geometric deep-learning techniques, there has been a dedicated effort to create mesh-based convolutional operators that act as a link between irregular mesh structures and widely adopted backbone networks. Despite the numerous advantages of Convolutional Neural Networks (CNNs) over Multi-Layer Perceptrons (MLPs), mesh-oriented CNNs often require intricate network architectures to tackle irregularities of a triangular mesh. These architectures not only demand that the mesh be manifold and watertight but also impose constraints on the abundance of training samples. In this paper, we note that for specific tasks such as mesh classification and semantic part segmentation, large-scale shape features play a pivotal role. This is in contrast to the realm of shape correspondence, where a comprehensive understanding of 3D shapes necessitates considering both local and global characteristics. Inspired by this key observation, we introduce a task-driven neural network architecture that seamlessly operates in an end-to-end fashion. Our method takes as input mesh vertices equipped with the heat kernel signature (HKS) and dihedral angles between adjacent faces. Notably, we replace the conventional convolutional module, commonly found in ResNet architectures, with MLPs and incorporate Layer Normalization (LN) to facilitate layer-wise normalization. Our approach, with a seemingly straightforward network architecture, demonstrates an accuracy advantage. It exhibits a marginal 0.1% improvement in the mesh classification task and a substantial 1.8% enhancement in the mesh part segmentation task compared to state-of-the-art methodologies. Moreover, as the number of training samples decreases to 1/50 or even 1/100, the accuracy advantage of our approach becomes more pronounced. In summary, our convolution-free network is tailored for specific tasks relying on large-scale shape features and excels in the situation with a limited number of training samples, setting itself apart from state-of-the-art methodologies.</p></div>","PeriodicalId":55226,"journal":{"name":"Computer Aided Geometric Design","volume":"111 ","pages":"Article 102304"},"PeriodicalIF":1.5,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140645561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-24DOI: 10.1016/j.cagd.2024.102308
Hua Wang , Fan Zhang
To construct a parametric polynomial curve for interpolating a set of data points, the interpolation accuracy and shape of the constructed curve are influenced by two principal factors: parameterization of the data points (computing a node for each data point) and interpolation method. A new method of computing nodes for a set of data points was proposed. In this paper, the functional relationship between data points and corresponding nodes in cubic polynomials was established. Using this functional relationship, a functional cubic polynomial with one degree of freedom can pass through four adjacent data points. The degree of the freedom can be represented by two adjacent node intervals can be obtained by minimizing the cubic terms of the cubic polynomial. Since each node is computed in different node spaces, a method for constructing a quadratic curve is presented, which transforms all the quadratic curves into a unified form to compute nodes. Nodes computed using the new method exhibit quadratic polynomial precision, i.e., if the set of data point is taken from a quadratic polynomial , the nodes by the new method are used to construct a interpolation curve, an interpolation method reproducing quadratic polynomial gives quadratic polynomial . The primary advantage of the proposed method is that the constructed curve has a shape described by data points. Another advantage of the new method is that the nodes computed by it have affine invariance. The experimental results indicate that the curve constructed by the nodes using the new method has a better interpolation accuracy and shape compared to that constructed using other methods.
{"title":"Computing nodes for plane data points by constructing cubic polynomial with constraints","authors":"Hua Wang , Fan Zhang","doi":"10.1016/j.cagd.2024.102308","DOIUrl":"https://doi.org/10.1016/j.cagd.2024.102308","url":null,"abstract":"<div><p>To construct a parametric polynomial curve for interpolating a set of data points, the interpolation accuracy and shape of the constructed curve are influenced by two principal factors: parameterization of the data points (computing a node for each data point) and interpolation method. A new method of computing nodes for a set of data points was proposed. In this paper, the functional relationship between data points and corresponding nodes in cubic polynomials was established. Using this functional relationship, a functional cubic polynomial with one degree of freedom can pass through four adjacent data points. The degree of the freedom can be represented by two adjacent node intervals can be obtained by minimizing the cubic terms of the cubic polynomial. Since each node is computed in different node spaces, a method for constructing a quadratic curve is presented, which transforms all the quadratic curves into a unified form to compute nodes. Nodes computed using the new method exhibit quadratic polynomial precision, i.e., if the set of data point is taken from a quadratic polynomial <span><math><mi>F</mi><mo>(</mo><mi>t</mi><mo>)</mo></math></span>, the nodes by the new method are used to construct a interpolation curve, an interpolation method reproducing quadratic polynomial gives quadratic polynomial <span><math><mi>F</mi><mo>(</mo><mi>t</mi><mo>)</mo></math></span>. The primary advantage of the proposed method is that the constructed curve has a shape described by data points. Another advantage of the new method is that the nodes computed by it have affine invariance. The experimental results indicate that the curve constructed by the nodes using the new method has a better interpolation accuracy and shape compared to that constructed using other methods.</p></div>","PeriodicalId":55226,"journal":{"name":"Computer Aided Geometric Design","volume":"111 ","pages":"Article 102308"},"PeriodicalIF":1.5,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140649954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-24DOI: 10.1016/j.cagd.2024.102312
Chengzhi Liu , Nian-Ci Wu , Juncheng Li , Lijuan Hu
This paper introduces two improved variants of the least squares progressive-iterative approximation (LSPIA) by leveraging momentum techniques. Specifically, based on the Polyak's and Nesterov's momentum techniques, the proposed methods utilize the previous iteration information to update the control points. We name these two methods PmLSPIA and NmLSPIA, respectively. The introduction of momentum enhances the determination of the search directions, leading to a significant improvement in convergence rate. The geometric interpretations of PmLSPIA and NmLSPIA are elucidated, providing insights into the underlying principles of these accelerated algorithms. Rigorous convergence analyses are conducted, revealing that both PmLSPIA and NmLSPIA exhibit faster convergence than LSPIA. Numerical results further validate the efficacy of the proposed algorithms.
{"title":"Two novel iterative approaches for improved LSPIA convergence","authors":"Chengzhi Liu , Nian-Ci Wu , Juncheng Li , Lijuan Hu","doi":"10.1016/j.cagd.2024.102312","DOIUrl":"https://doi.org/10.1016/j.cagd.2024.102312","url":null,"abstract":"<div><p>This paper introduces two improved variants of the least squares progressive-iterative approximation (LSPIA) by leveraging momentum techniques. Specifically, based on the Polyak's and Nesterov's momentum techniques, the proposed methods utilize the previous iteration information to update the control points. We name these two methods PmLSPIA and NmLSPIA, respectively. The introduction of momentum enhances the determination of the search directions, leading to a significant improvement in convergence rate. The geometric interpretations of PmLSPIA and NmLSPIA are elucidated, providing insights into the underlying principles of these accelerated algorithms. Rigorous convergence analyses are conducted, revealing that both PmLSPIA and NmLSPIA exhibit faster convergence than LSPIA. Numerical results further validate the efficacy of the proposed algorithms.</p></div>","PeriodicalId":55226,"journal":{"name":"Computer Aided Geometric Design","volume":"111 ","pages":"Article 102312"},"PeriodicalIF":1.5,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140649956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-23DOI: 10.1016/j.cagd.2024.102297
Jingjing Yang , Chun-Gang Zhu
Implicit representations possess many merits when dealing with geometries with certain properties, such as small holes, reentrant corners and other complex details. Truncated hierarchical B-splines (THB-splines) has recently emerged as a novel tool in many fields including design and analysis due to its local refinement ability. In this paper, we propose an adaptive collocation method with weighted extended THB-splines (WETHB-splines) on implicit domains. We modify the classification strategy for the WETHB-basis, and the centers of the supports of inner THB-splines on each level are chosen to be collocation points. We also use weighted collocation in the transition regions, in order to enrich information concerning the hierarchical basis. In contrast to the traditional WEB-collocation method, the proposed approach possesses much higher convergence rate. To show the efficiency and superiority of the proposed method, numerical examples in two and three dimensions are performed to solve Poisson's equations.
在处理具有某些特性的几何图形(如小孔、重入角和其他复杂细节)时,隐式表示法具有许多优点。截断分层 B 样条曲线(THB 样条曲线)因其局部细化能力,最近已成为设计和分析等许多领域的新工具。在本文中,我们提出了一种在隐式域上使用加权扩展 THB 样条线(WETHB 样条线)的自适应配准方法。我们修改了 WETHB 基准的分类策略,并选择每一级内 THB 样条曲线的支撑中心作为配准点。我们还在过渡区域使用加权配准,以丰富分层基础的相关信息。与传统的 WEB 拼合方法相比,所提出的方法具有更高的收敛率。为了证明所提方法的效率和优越性,我们用二维和三维数值实例求解了泊松方程。
{"title":"An adaptive collocation method on implicit domains using weighted extended THB-splines","authors":"Jingjing Yang , Chun-Gang Zhu","doi":"10.1016/j.cagd.2024.102297","DOIUrl":"10.1016/j.cagd.2024.102297","url":null,"abstract":"<div><p>Implicit representations possess many merits when dealing with geometries with certain properties, such as small holes, reentrant corners and other complex details. Truncated hierarchical B-splines (THB-splines) has recently emerged as a novel tool in many fields including design and analysis due to its local refinement ability. In this paper, we propose an adaptive collocation method with weighted extended THB-splines (WETHB-splines) on implicit domains. We modify the classification strategy for the WETHB-basis, and the centers of the supports of inner THB-splines on each level are chosen to be collocation points. We also use weighted collocation in the transition regions, in order to enrich information concerning the hierarchical basis. In contrast to the traditional WEB-collocation method, the proposed approach possesses much higher convergence rate. To show the efficiency and superiority of the proposed method, numerical examples in two and three dimensions are performed to solve Poisson's equations.</p></div>","PeriodicalId":55226,"journal":{"name":"Computer Aided Geometric Design","volume":"111 ","pages":"Article 102297"},"PeriodicalIF":1.5,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140785011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-23DOI: 10.1016/j.cagd.2024.102299
Zhiyuan Ren , Long Ma , Minfeng Xu , Guangshun Wei , Shaojie Zhuang , Yuanfeng Zhou
In digital orthodontic treatment, the high-precision reconstruction of complete teeth, encompassing both the crown and the actual root, plays a pivotal role. Current mainstream techniques, prioritizing the high resolution of intraoral scanned models (IOS), are confined to using IOS data for orthodontic treatments. However, the lack of root information in the IOS data may lead to complications such as dehiscence. In contrast, Cone Beam Computed Tomography (CBCT) data encompasses comprehensive dental information with roots. Nonetheless, the radiative character of CBCT scans renders patients unsuitable for repeated examinations in a short time. In addition, lower scanning precision of CBCT leads to suboptimal teeth segmentation outcomes, hindering the accurate representation of dental occlusal relationships. Therefore, in order to fully utilize the complementarity between dental multimodal data, we propose a method for high-precision 3D teeth model reconstruction based on IOS and CBCT, which mainly consists of global rigid registration and local nonrigid registration. Specifically, we extract the priori information of dental arch curves for coarse alignment to provide a good initial position for the Iterative Closest Point (ICP) algorithm, and design a conformal parameterization method for a single tooth to effectively obtain the point correspondence between IOS and CBCT crowns. The rough crown of the CBCT will gradually fit towards the IOS through iterative optimization of nonrigid registration. The experimental results show that our method robustly fuses the advantageous features of IOS and CBCT. The 3D teeth model reconstructed by our method contains the high-precision crown of IOS and the real root of CBCT, which can be effectively used in clinical orthodontic treatment.
{"title":"High-precision teeth reconstruction based on automatic multimodal fusion with CBCT and IOS","authors":"Zhiyuan Ren , Long Ma , Minfeng Xu , Guangshun Wei , Shaojie Zhuang , Yuanfeng Zhou","doi":"10.1016/j.cagd.2024.102299","DOIUrl":"https://doi.org/10.1016/j.cagd.2024.102299","url":null,"abstract":"<div><p>In digital orthodontic treatment, the high-precision reconstruction of complete teeth, encompassing both the crown and the actual root, plays a pivotal role. Current mainstream techniques, prioritizing the high resolution of intraoral scanned models (IOS), are confined to using IOS data for orthodontic treatments. However, the lack of root information in the IOS data may lead to complications such as dehiscence. In contrast, Cone Beam Computed Tomography (CBCT) data encompasses comprehensive dental information with roots. Nonetheless, the radiative character of CBCT scans renders patients unsuitable for repeated examinations in a short time. In addition, lower scanning precision of CBCT leads to suboptimal teeth segmentation outcomes, hindering the accurate representation of dental occlusal relationships. Therefore, in order to fully utilize the complementarity between dental multimodal data, we propose a method for high-precision 3D teeth model reconstruction based on IOS and CBCT, which mainly consists of global rigid registration and local nonrigid registration. Specifically, we extract the priori information of dental arch curves for coarse alignment to provide a good initial position for the Iterative Closest Point (ICP) algorithm, and design a conformal parameterization method for a single tooth to effectively obtain the point correspondence between IOS and CBCT crowns. The rough crown of the CBCT will gradually fit towards the IOS through iterative optimization of nonrigid registration. The experimental results show that our method robustly fuses the advantageous features of IOS and CBCT. The 3D teeth model reconstructed by our method contains the high-precision crown of IOS and the real root of CBCT, which can be effectively used in clinical orthodontic treatment.</p></div>","PeriodicalId":55226,"journal":{"name":"Computer Aided Geometric Design","volume":"111 ","pages":"Article 102299"},"PeriodicalIF":1.5,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140645559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-23DOI: 10.1016/j.cagd.2024.102301
Zhaobin Huang, Shibo Liu, Xiao-Ming Fu
We propose a simple yet effective method to interpolate high-order meshes. Given two manifold high-order triangular (or tetrahedral) meshes with identical connectivity, our goal is to generate a continuum of curved shapes with as little distortion as possible in the mapping from the source mesh to the interpolated mesh. Our algorithm contains two steps: (1) linearly blend the pullback metric of the identity mapping and the input mapping between two Bézier elements on a set of sampling points; (2) project the interpolated metric into the metric space between Bézier elements using the Newton method for nonlinear optimization. We demonstrate the feasibility and practicability of the method for high-order meshes through extensive experiments in both 2D and 3D.
{"title":"High-order shape interpolation","authors":"Zhaobin Huang, Shibo Liu, Xiao-Ming Fu","doi":"10.1016/j.cagd.2024.102301","DOIUrl":"https://doi.org/10.1016/j.cagd.2024.102301","url":null,"abstract":"<div><p>We propose a simple yet effective method to interpolate high-order meshes. Given two manifold high-order triangular (or tetrahedral) meshes with identical connectivity, our goal is to generate a continuum of curved shapes with as little distortion as possible in the mapping from the source mesh to the interpolated mesh. Our algorithm contains two steps: (1) linearly blend the pullback metric of the identity mapping and the input mapping between two Bézier elements on a set of sampling points; (2) project the interpolated metric into the metric space between Bézier elements using the Newton method for nonlinear optimization. We demonstrate the feasibility and practicability of the method for high-order meshes through extensive experiments in both 2D and 3D.</p></div>","PeriodicalId":55226,"journal":{"name":"Computer Aided Geometric Design","volume":"111 ","pages":"Article 102301"},"PeriodicalIF":1.5,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140641086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-23DOI: 10.1016/j.cagd.2024.102296
Xiaopeng Sun , Shihan Liu , Zhiqiang Luo , Zhongtai Yang
The structural design of 3D auxetic linkages is a burgeoning field in digital manufacturing. This article presents a novel algorithm for designing 3D auxetic linkage structures based on Kirigami principles to address existing limitations. The 3D input model is initially mapped to a 2D space using conformal mapping based on the BFF method. This is followed by 2D re-meshing using an equilateral triangle mesh. Subsequently, a 3D topological mesh of the auxetic linkage is calculated through inverse mapping based on directed area. We then introduce new basic rotating and non-rotating units, employing them as the initial structure of the 3D auxetic linkage in accordance with Kirigami techniques. Lastly, a deformation energy function is defined to optimize the shape of the rotating units. The vertex coordinates of the non-rotating units are updated according to the optimized positions of the rotating units, thereby generating an optimal 3D auxetic linkage structure. Experimental results validate the effectiveness and accuracy of our algorithm. Quantitative analyses of structural porosity and optimization accuracy, as well as comparisons with related works, indicate that our algorithm yields structures with smaller shape errors.
{"title":"3D auxetic linkage based on Kirigami","authors":"Xiaopeng Sun , Shihan Liu , Zhiqiang Luo , Zhongtai Yang","doi":"10.1016/j.cagd.2024.102296","DOIUrl":"10.1016/j.cagd.2024.102296","url":null,"abstract":"<div><p>The structural design of 3D auxetic linkages is a burgeoning field in digital manufacturing. This article presents a novel algorithm for designing 3D auxetic linkage structures based on Kirigami principles to address existing limitations. The 3D input model is initially mapped to a 2D space using conformal mapping based on the BFF method. This is followed by 2D re-meshing using an equilateral triangle mesh. Subsequently, a 3D topological mesh of the auxetic linkage is calculated through inverse mapping based on directed area. We then introduce new basic rotating and non-rotating units, employing them as the initial structure of the 3D auxetic linkage in accordance with Kirigami techniques. Lastly, a deformation energy function is defined to optimize the shape of the rotating units. The vertex coordinates of the non-rotating units are updated according to the optimized positions of the rotating units, thereby generating an optimal 3D auxetic linkage structure. Experimental results validate the effectiveness and accuracy of our algorithm. Quantitative analyses of structural porosity and optimization accuracy, as well as comparisons with related works, indicate that our algorithm yields structures with smaller shape errors.</p></div>","PeriodicalId":55226,"journal":{"name":"Computer Aided Geometric Design","volume":"111 ","pages":"Article 102296"},"PeriodicalIF":1.5,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140797353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}