Pub Date : 2025-02-04DOI: 10.1016/j.gmod.2025.101255
Changshuang Zhou , Frederick W.B. Li , Chao Song , Dong Zheng , Bailin Yang
We propose Dual-Branch Network (DBNet), a novel deepfake detection framework that addresses key limitations of existing works by jointly modeling 3D-temporal and fine-grained texture representations. Specifically, we aim to investigate how to (1) capture dynamic properties and spatial details in a unified model and (2) identify subtle inconsistencies beyond localized artifacts through temporally consistent modeling. To this end, DBNet extracts 3D landmarks from videos to construct temporal sequences for an RNN branch, while a Vision Transformer analyzes local patches. A Temporal Consistency-aware Loss is introduced to explicitly supervise the RNN. Additionally, a 3D generative model augments training data. Extensive experiments demonstrate our method achieves state-of-the-art performance on benchmarks, and ablation studies validate its effectiveness in generalizing to unseen data under various manipulations and compression.
{"title":"3D data augmentation and dual-branch model for robust face forgery detection","authors":"Changshuang Zhou , Frederick W.B. Li , Chao Song , Dong Zheng , Bailin Yang","doi":"10.1016/j.gmod.2025.101255","DOIUrl":"10.1016/j.gmod.2025.101255","url":null,"abstract":"<div><div>We propose Dual-Branch Network (DBNet), a novel deepfake detection framework that addresses key limitations of existing works by jointly modeling 3D-temporal and fine-grained texture representations. Specifically, we aim to investigate how to (1) capture dynamic properties and spatial details in a unified model and (2) identify subtle inconsistencies beyond localized artifacts through temporally consistent modeling. To this end, DBNet extracts 3D landmarks from videos to construct temporal sequences for an RNN branch, while a Vision Transformer analyzes local patches. A Temporal Consistency-aware Loss is introduced to explicitly supervise the RNN. Additionally, a 3D generative model augments training data. Extensive experiments demonstrate our method achieves state-of-the-art performance on benchmarks, and ablation studies validate its effectiveness in generalizing to unseen data under various manipulations and compression.</div></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"138 ","pages":"Article 101255"},"PeriodicalIF":2.5,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143104630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.gmod.2024.101253
Manuel Prado-Velasco, Laura García-Ruesgas
The Computer extended Descriptive Geometry (CeDG) is as a novel approach based on Descriptive Geometry to build 3D models within the framework provided by Dynamic Geometry Software tools. Parametric CeDG models can be interactively explored when continuous parameters change, but this is not the case for discrete parameters. This study demonstrates the capability of the GeoGebra - CeDG approach to incorporate algorithms that build discrete variable 3D models with dynamic parameterization. Several 3D models and their flattened patterns (neutral fiber), based on a new developed CeDG algorithm, were compared to their LogiTRACE v.14 and Solid Edge 2024 (CAD) counterparts. The accuracy of the CeDG models surpassed that of CAD models for nearly all dimensions defined as metrics. In addition, the CeDG approach was the unique that provided an automatic solution for any value of the number of ferrules.
{"title":"Discrete variable 3D models in Computer extended Descriptive Geometry (CeDG): Building of polygonal sheet-metal elbows and comparison against CAD","authors":"Manuel Prado-Velasco, Laura García-Ruesgas","doi":"10.1016/j.gmod.2024.101253","DOIUrl":"10.1016/j.gmod.2024.101253","url":null,"abstract":"<div><div>The Computer extended Descriptive Geometry (CeDG) is as a novel approach based on Descriptive Geometry to build 3D models within the framework provided by Dynamic Geometry Software tools. Parametric CeDG models can be interactively explored when continuous parameters change, but this is not the case for discrete parameters. This study demonstrates the capability of the GeoGebra - CeDG approach to incorporate algorithms that build discrete variable 3D models with dynamic parameterization. Several 3D models and their flattened patterns (neutral fiber), based on a new developed CeDG algorithm, were compared to their LogiTRACE v.14 and Solid Edge 2024 (CAD) counterparts. The accuracy of the CeDG models surpassed that of CAD models for nearly all dimensions defined as metrics. In addition, the CeDG approach was the unique that provided an automatic solution for any value of the number of ferrules.</div></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"137 ","pages":"Article 101253"},"PeriodicalIF":2.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143140781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.gmod.2024.101251
Carlotta Giannelli , Sofia Imperatore , Angelos Mantzaflaris , Dominik Mokriš
We propose a new paradigm for scattered data fitting with adaptive spline constructions based on the key interplay between parameterization and adaptivity. Specifically, we introduce two novel adaptive fitting schemes that combine moving parameterizations with adaptive spline refinement for highly accurate CAD models reconstruction from real-world scattered point clouds. The first scheme alternates surface fitting and data parameter optimization. The second scheme jointly optimizes the parameters and the surface control points. To combine the proposed fitting methods with adaptive spline constructions, we present a key treatment of boundary points. Industrial examples show that updating the parameterization, within an adaptive spline approximation framework, significantly reduces the number of degrees of freedom needed for a certain accuracy, especially if spline adaptivity is driven by suitably graded hierarchical meshes. The numerical experiments employ THB-splines, thus exploiting the existing CAD integration within the considered industrial setting, nevertheless, any adaptive spline construction can be chosen.
{"title":"Efficient alternating and joint distance minimization methods for adaptive spline surface fitting","authors":"Carlotta Giannelli , Sofia Imperatore , Angelos Mantzaflaris , Dominik Mokriš","doi":"10.1016/j.gmod.2024.101251","DOIUrl":"10.1016/j.gmod.2024.101251","url":null,"abstract":"<div><div>We propose a new paradigm for scattered data fitting with adaptive spline constructions based on the key interplay between parameterization and adaptivity. Specifically, we introduce two novel adaptive fitting schemes that combine moving parameterizations with adaptive spline refinement for highly accurate CAD models reconstruction from real-world scattered point clouds. The first scheme alternates surface fitting and data parameter optimization. The second scheme jointly optimizes the parameters and the surface control points. To combine the proposed fitting methods with adaptive spline constructions, we present a key treatment of boundary points. Industrial examples show that updating the parameterization, within an adaptive spline approximation framework, significantly reduces the number of degrees of freedom needed for a certain accuracy, especially if spline adaptivity is driven by suitably graded hierarchical meshes. The numerical experiments employ THB-splines, thus exploiting the existing CAD integration within the considered industrial setting, nevertheless, any adaptive spline construction can be chosen.</div></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"137 ","pages":"Article 101251"},"PeriodicalIF":2.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143140780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.gmod.2024.101239
Francesco Ballerin, Erlend Grong
Equipping the rototranslation group SE(2) with a sub-Riemannian structure inspired by the visual cortex V1, we propose algorithms for image inpainting and enhancement based on hypoelliptic diffusion. We innovate on previous implementations of the methods by Citti, Sarti, and Boscain et al., by proposing an alternative that prevents fading and is capable of producing sharper results in a procedure that we call WaxOn-WaxOff. We also exploit the sub-Riemannian structure to define a completely new unsharp filter using SE(2), analogous to the classical unsharp filter for 2D image processing. We demonstrate our method on blood vessels enhancement in retinal scans.
{"title":"Geometry of the visual cortex with applications to image inpainting and enhancement","authors":"Francesco Ballerin, Erlend Grong","doi":"10.1016/j.gmod.2024.101239","DOIUrl":"10.1016/j.gmod.2024.101239","url":null,"abstract":"<div><div>Equipping the rototranslation group SE(2) with a sub-Riemannian structure inspired by the visual cortex V1, we propose algorithms for image inpainting and enhancement based on hypoelliptic diffusion. We innovate on previous implementations of the methods by Citti, Sarti, and Boscain et al., by proposing an alternative that prevents fading and is capable of producing sharper results in a procedure that we call <span>WaxOn</span>-<span>WaxOff</span>. We also exploit the sub-Riemannian structure to define a completely new unsharp filter using SE(2), analogous to the classical unsharp filter for 2D image processing. We demonstrate our method on blood vessels enhancement in retinal scans.</div></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"137 ","pages":"Article 101239"},"PeriodicalIF":2.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143140783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.gmod.2024.101250
Hailun Xu, Zepeng Wen, Hongmei Kang
Subdivision surfaces as an extension of splines have become a promising technique for addressing PDEs on models with complex topologies in isogeometric analysis. This has sparked interest in exploring the approximation by subdivision function spaces. Quasi-interpolation serves as a significant tool in the field of approximation, offering benefits such as low computational expense and strong numerical stability. In this paper, we propose a straightforward approach for constructing the quasi-interpolation projectors of subdivision function spaces that features explicit formulations and achieves a highly desirable approximation order. The local interpolation problem is constructed based on the subdivision mask and the limit position mask, overcoming the cumbersome evaluation of the subdivision basis functions and the difficulty associated with deriving explicit solutions to the problem. Explicit quasi-interpolation formulas for the loop, modified loop, and Catmull–Clark subdivisions are provided. Numerical experiments demonstrate that these quasi-interpolation projectors achieve an expected approximate order and present promising prospects in isogeometric collocation.
{"title":"Quasi-interpolation projectors for subdivision function spaces","authors":"Hailun Xu, Zepeng Wen, Hongmei Kang","doi":"10.1016/j.gmod.2024.101250","DOIUrl":"10.1016/j.gmod.2024.101250","url":null,"abstract":"<div><div>Subdivision surfaces as an extension of splines have become a promising technique for addressing PDEs on models with complex topologies in isogeometric analysis. This has sparked interest in exploring the approximation by subdivision function spaces. Quasi-interpolation serves as a significant tool in the field of approximation, offering benefits such as low computational expense and strong numerical stability. In this paper, we propose a straightforward approach for constructing the quasi-interpolation projectors of subdivision function spaces that features explicit formulations and achieves a highly desirable approximation order. The local interpolation problem is constructed based on the subdivision mask and the limit position mask, overcoming the cumbersome evaluation of the subdivision basis functions and the difficulty associated with deriving explicit solutions to the problem. Explicit quasi-interpolation formulas for the loop, modified loop, and Catmull–Clark subdivisions are provided. Numerical experiments demonstrate that these quasi-interpolation projectors achieve an expected approximate order and present promising prospects in isogeometric collocation.</div></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"137 ","pages":"Article 101250"},"PeriodicalIF":2.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143140779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.gmod.2024.101252
Linjun Jiang , Yue Liu , Zhiyuan Dong , Yinghao Li , Yusong Lin
Point cloud registration, a fundamental task in computer science and artificial intelligence, involves rigidly transforming point clouds from different perspectives into a common coordinate system. Traditional registration methods often lack robustness and fail to achieve the desired level of accuracy. In contrast, deep learning-based registration methods have demonstrated improved accuracy and generalization. However, these methods are hindered by large parameter sizes, complex network architectures, and challenges related to efficiency, robustness, and partial overlaps. In this study, we propose a lightweight deep learning-based registration method that captures features from multiple perspectives to predict overlapping points and mitigate the interference of non-overlapping points. Specifically, our approach utilizes pruning and weight-sharing quantization techniques to reduce model size and simplify the network structure. We evaluate the proposed model on noisy and partially overlapping point clouds from the ModelNet40 dataset, comparing its performance against other existing methods. Experimental results show that the proposed method significantly reduces the model's parameter size without compromising registration accuracy.
{"title":"Lightweight deep learning method for end-to-end point cloud registration","authors":"Linjun Jiang , Yue Liu , Zhiyuan Dong , Yinghao Li , Yusong Lin","doi":"10.1016/j.gmod.2024.101252","DOIUrl":"10.1016/j.gmod.2024.101252","url":null,"abstract":"<div><div>Point cloud registration, a fundamental task in computer science and artificial intelligence, involves rigidly transforming point clouds from different perspectives into a common coordinate system. Traditional registration methods often lack robustness and fail to achieve the desired level of accuracy. In contrast, deep learning-based registration methods have demonstrated improved accuracy and generalization. However, these methods are hindered by large parameter sizes, complex network architectures, and challenges related to efficiency, robustness, and partial overlaps. In this study, we propose a lightweight deep learning-based registration method that captures features from multiple perspectives to predict overlapping points and mitigate the interference of non-overlapping points. Specifically, our approach utilizes pruning and weight-sharing quantization techniques to reduce model size and simplify the network structure. We evaluate the proposed model on noisy and partially overlapping point clouds from the ModelNet40 dataset, comparing its performance against other existing methods. Experimental results show that the proposed method significantly reduces the model's parameter size without compromising registration accuracy.</div></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"137 ","pages":"Article 101252"},"PeriodicalIF":2.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143140782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-28DOI: 10.1016/j.gmod.2025.101254
Khang Yeu Tang , Ge Yu , Juhong Wang , Yu He , Sen-Zhe Xu , Song-Hai Zhang
As technology advances, user demand for immersive and authentic information presentation rises. Traditional 2D displays and interactions fail to meet modern standards, while virtual reality (VR) is gaining attention for its immersive experience. However, using a controller for VR movement can cause dizziness due to mismatched visual and vestibular cues, impacting the VR experience. This paper analyzes the main causes of VR-induced vertigo and develops improved handheld controller movement strategies. These strategies adjust the user’s pitch angle and field of view in real time or map the user’s real-world head acceleration to the virtual character. By intelligently adjusting the controller-to-VR display mapping, these methods reduce vertigo. In addition, this paper also verified the actual effects of these designs through a series of experiments, and conducted detailed data analysis on the degree of user vertigo. The experimental results showed that using a specific improved handheld controller movement design can significantly improve the user’s comfort in the VR environment, effectively reducing the occurrence of vertigo and discomfort.
{"title":"Strategies for reducing motion sickness in virtual reality through improved handheld controller movements","authors":"Khang Yeu Tang , Ge Yu , Juhong Wang , Yu He , Sen-Zhe Xu , Song-Hai Zhang","doi":"10.1016/j.gmod.2025.101254","DOIUrl":"10.1016/j.gmod.2025.101254","url":null,"abstract":"<div><div>As technology advances, user demand for immersive and authentic information presentation rises. Traditional 2D displays and interactions fail to meet modern standards, while virtual reality (VR) is gaining attention for its immersive experience. However, using a controller for VR movement can cause dizziness due to mismatched visual and vestibular cues, impacting the VR experience. This paper analyzes the main causes of VR-induced vertigo and develops improved handheld controller movement strategies. These strategies adjust the user’s pitch angle and field of view in real time or map the user’s real-world head acceleration to the virtual character. By intelligently adjusting the controller-to-VR display mapping, these methods reduce vertigo. In addition, this paper also verified the actual effects of these designs through a series of experiments, and conducted detailed data analysis on the degree of user vertigo. The experimental results showed that using a specific improved handheld controller movement design can significantly improve the user’s comfort in the VR environment, effectively reducing the occurrence of vertigo and discomfort.</div></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"138 ","pages":"Article 101254"},"PeriodicalIF":2.5,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143104629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-25DOI: 10.1016/j.gmod.2024.101237
Jieyi Chen , Zhen Wen , Li Zheng , Jiaying Lu , Hui Lu , Yiwen Ren , Wei Chen
Advanced quantum computers have the capability to perform practical quantum computing to address specific problems that are intractable for classical computers. Nevertheless, these computers are susceptible to noise, leading to unexpectable errors in outcomes, which makes them less trustworthy. To address this challenge, we propose HammingVis, a visual analytics approach that helps identify and understand errors in quantum outcomes. Given that these errors exhibit latent structural patterns within Hamming space, we introduce two graph visualizations to reveal these patterns from distinct perspectives. One highlights the overall structure of errors, while the other focuses on the impact of errors within important subspaces. We further develop a prototype system for interactively exploring and discerning the correct outcomes within Hamming space. A novel design is presented to distinguish the neighborhood patterns between error and correct outcomes. The effectiveness of our approach is demonstrated through case studies involving two classic quantum algorithms’ outcome data.
{"title":"HammingVis: A visual analytics approach for understanding erroneous outcomes of quantum computing in hamming space","authors":"Jieyi Chen , Zhen Wen , Li Zheng , Jiaying Lu , Hui Lu , Yiwen Ren , Wei Chen","doi":"10.1016/j.gmod.2024.101237","DOIUrl":"10.1016/j.gmod.2024.101237","url":null,"abstract":"<div><div>Advanced quantum computers have the capability to perform practical quantum computing to address specific problems that are intractable for classical computers. Nevertheless, these computers are susceptible to noise, leading to unexpectable errors in outcomes, which makes them less trustworthy. To address this challenge, we propose HammingVis, a visual analytics approach that helps identify and understand errors in quantum outcomes. Given that these errors exhibit latent structural patterns within Hamming space, we introduce two graph visualizations to reveal these patterns from distinct perspectives. One highlights the overall structure of errors, while the other focuses on the impact of errors within important subspaces. We further develop a prototype system for interactively exploring and discerning the correct outcomes within Hamming space. A novel design is presented to distinguish the neighborhood patterns between error and correct outcomes. The effectiveness of our approach is demonstrated through case studies involving two classic quantum algorithms’ outcome data.</div></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"136 ","pages":"Article 101237"},"PeriodicalIF":2.5,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142529388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Large language models (LLMs) like those that power OpenAI’s ChatGPT and Google’s Gemini have played a major part in the recent wave of machine learning and artificial intelligence advancements. However, interpreting LLMs and visualizing their components is extremely difficult due to the incredible scale and high dimensionality of model data. NeuronautLLM introduces a visual analysis system for identifying and visualizing influential neurons in transformer-based language models as they relate to user-defined prompts. Our approach combines simple, yet information-dense visualizations as well as neuron explanation and classification data to provide a wealth of opportunities for exploration. NeuronautLLM was reviewed by two experts to verify its efficacy as a tool for practical model interpretation. Interviews and usability tests with five LLM experts demonstrated NeuronautLLM’s exceptional usability and its readiness for real-world application. Furthermore, two in-depth case studies on model reasoning and social bias highlight NeuronautLLM’s versatility in aiding the analysis of a wide range of LLM research problems.
{"title":"Exploring the neural landscape: Visual analytics of neuron activation in large language models with NeuronautLLM","authors":"Ollie Woodman , Zhen Wen , Hui Lu , Yiwen Ren , Minfeng Zhu , Wei Chen","doi":"10.1016/j.gmod.2024.101238","DOIUrl":"10.1016/j.gmod.2024.101238","url":null,"abstract":"<div><div>Large language models (LLMs) like those that power OpenAI’s ChatGPT and Google’s Gemini have played a major part in the recent wave of machine learning and artificial intelligence advancements. However, interpreting LLMs and visualizing their components is extremely difficult due to the incredible scale and high dimensionality of model data. NeuronautLLM introduces a visual analysis system for identifying and visualizing influential neurons in transformer-based language models as they relate to user-defined prompts. Our approach combines simple, yet information-dense visualizations as well as neuron explanation and classification data to provide a wealth of opportunities for exploration. NeuronautLLM was reviewed by two experts to verify its efficacy as a tool for practical model interpretation. Interviews and usability tests with five LLM experts demonstrated NeuronautLLM’s exceptional usability and its readiness for real-world application. Furthermore, two in-depth case studies on model reasoning and social bias highlight NeuronautLLM’s versatility in aiding the analysis of a wide range of LLM research problems.</div></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"136 ","pages":"Article 101238"},"PeriodicalIF":2.5,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142529389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-19DOI: 10.1016/j.gmod.2024.101236
Bingchuan Li , Yuping Ye , Junfeng Yao , Yong Yang , Weixing Xie , Mengyuan Ge
The medial axis transform (MAT) of an object is the set of all points inside the object that have more than one closest point on the object’s boundary. Representing sharp edges and corners of triangular meshes using MAT poses a complex challenge. While some researchers have proposed using zero-radius medial spheres to depict these features, they have not clearly articulated how to establish proper connections among them. In this paper, we propose a novel framework for computing MAT of a triangular mesh while preserving its features. The initial medial axis mesh obtained may contain erroneous edges, which are discussed and addressed in Section 3.3. Furthermore, during the simplification process, it is crucial to ensure that the medial spheres remain within the confines of the triangular mesh. Our algorithm excels in preserving critical features throughout the simplification procedure, consistently ensuring that the spheres remain enclosed within the triangular mesh. Experiments on various types of 3D models demonstrate the robustness, shape fidelity, and efficiency in representation achieved by our algorithm.
对象的中轴变换（MAT）是对象内部所有点的集合，这些点在对象边界上有一个以上的最近点。使用 MAT 表示三角形网格的锐边和锐角是一项复杂的挑战。虽然一些研究人员提出使用零半径中轴球来描述这些特征，但他们并没有明确阐述如何在这些特征之间建立适当的连接。在本文中，我们提出了一种新颖的框架，用于计算三角形网格的 MAT，同时保留其特征。获得的初始中轴网格可能包含错误的边，这将在第 3.3 节中讨论和解决。此外，在简化过程中，确保中轴球体保持在三角形网格范围内至关重要。我们的算法能在整个简化过程中出色地保留关键特征，始终确保球体保持在三角形网格内。对各种类型的三维模型进行的实验证明了我们的算法在稳健性、形状保真度和表示效率方面的优势。
{"title":"A detail-preserving method for medial mesh computation in triangular meshes","authors":"Bingchuan Li , Yuping Ye , Junfeng Yao , Yong Yang , Weixing Xie , Mengyuan Ge","doi":"10.1016/j.gmod.2024.101236","DOIUrl":"10.1016/j.gmod.2024.101236","url":null,"abstract":"<div><div>The medial axis transform (MAT) of an object is the set of all points inside the object that have more than one closest point on the object’s boundary. Representing sharp edges and corners of triangular meshes using MAT poses a complex challenge. While some researchers have proposed using zero-radius medial spheres to depict these features, they have not clearly articulated how to establish proper connections among them. In this paper, we propose a novel framework for computing MAT of a triangular mesh while preserving its features. The initial medial axis mesh obtained may contain erroneous edges, which are discussed and addressed in Section 3.3. Furthermore, during the simplification process, it is crucial to ensure that the medial spheres remain within the confines of the triangular mesh. Our algorithm excels in preserving critical features throughout the simplification procedure, consistently ensuring that the spheres remain enclosed within the triangular mesh. Experiments on various types of 3D models demonstrate the robustness, shape fidelity, and efficiency in representation achieved by our algorithm.</div></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"136 ","pages":"Article 101236"},"PeriodicalIF":2.5,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142529387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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