Graphical Models最新文献

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Efficient extraction of experimental data from line charts using advanced machine learning techniques 利用先进的机器学习技术从折线图中高效提取实验数据

IF 2.5 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Graphical Models

Pub Date : 2025-03-25 DOI: 10.1016/j.gmod.2025.101259

Wenjin Yang, Jie He, Xiaotong Zhang

Line charts, as a common data visualization tool in scientific research and business analysis, encapsulate rich experimental data. However, existing data extraction tools face challenges such as low automation levels and difficulties in handling complex charts. This paper proposes a novel method for extracting data from line charts, reformulating the extraction problem as an instance segmentation task, and introducing the Mamba-enhanced Transformer mask query method along with a curve mask-guided training approach to address challenges such as long dependencies and intersections in curve detection. Additionally, YOLOv9 is utilized for the detection and classification of chart elements, and a text recognition dataset comprising approximately 100K charts is constructed. An LSTM-based attention mechanism is employed for precise scale value recognition. Lastly, we present a method for automatically converting image data into structured JSON data, significantly enhancing the efficiency and accuracy of data extraction. Experimental results demonstrate that this method exhibits high efficiency and accuracy in handling complex charts, achieving an average extraction accuracy of 93% on public datasets, significantly surpassing the current state-of-the-art methods. This research provides an efficient foundation for large-scale scientific data analysis and machine learning model development, advancing the field of automated data extraction technology.

折线图作为科学研究和商业分析中常用的数据可视化工具，封装了丰富的实验数据。然而，现有的数据提取工具面临着自动化水平低和处理复杂图表困难等挑战。本文提出了一种从折线图中提取数据的新方法，将提取问题重新定义为实例分割任务，并引入了mamba增强的Transformer掩码查询方法以及曲线掩码指导的训练方法，以解决曲线检测中的长依赖关系和交叉点等挑战。此外，利用YOLOv9对图表元素进行检测和分类，构建了包含约100K个图表的文本识别数据集。采用基于lstm的注意机制进行尺度值的精确识别。最后，我们提出了一种将图像数据自动转换为结构化JSON数据的方法，大大提高了数据提取的效率和准确性。实验结果表明，该方法在处理复杂图表方面具有较高的效率和准确性，在公共数据集上的平均提取准确率达到93%，大大超过了目前最先进的方法。本研究为大规模科学数据分析和机器学习模型开发提供了有效的基础，推动了自动化数据提取技术领域的发展。

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引用次数: 0

Computing medial axis of a simple polygon in linear time based on R-L sequence 基于R-L序列在线性时间内计算简单多边形的中轴线

IF 2.5 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Graphical Models

Pub Date : 2025-03-24 DOI: 10.1016/j.gmod.2025.101258

Hongyu Chen, Xiaodiao Chen, Yizhao Xue

Medial axis computation has wide applications in pattern recognition, image processing, finite element mesh generation, and CNC tool path extraction. Aiming to explore intrinsic geometric attributes of the medial axis of a simple polygon which can be accurately represented and faces its challenge of computational efficiency, an R-L sequence-based algorithm of linear computational complexity is proposed for achieving much higher efficiency; especially, it enables the complexity of Delaunay triangulation to be linear. The algorithm is done by reconstructing the Voronoi diagram tree of the given simple polygon, which can be easily performed in a breadth-first manner with a higher computational efficiency. The branches of the medial axis are naturally divided into several panels, such that the branches in the same panel cause no interference with each other and decrease a lot of computational costs. Based on our experiments, the efficiency of the proposed R-L algorithm can be 6 to 17 times greater than that of the state-of-the-art method in TVCG, and up to 419 times greater than the CGAL algorithm. In principle, it can be directly applied to compute the medial axis of curvilinear polygons, which expands the scope of application compared to Chin’s method.

中轴计算在模式识别、图像处理、有限元网格生成和数控刀具路径提取中有着广泛的应用。为了探索可精确表示的简单多边形中轴线的内在几何属性，面对其计算效率的挑战，提出了一种基于 R-L 序列的线性计算复杂度算法，以实现更高的效率，特别是使 Delaunay 三角剖分的复杂度成为线性。该算法通过重建给定简单多边形的 Voronoi 图树来完成，可以轻松地以广度优先的方式执行，具有更高的计算效率。中轴的分支被自然地划分为多个板块，这样同一板块中的分支就不会相互干扰，从而降低了大量的计算成本。根据我们的实验，所提出的 R-L 算法的效率是 TVCG 中最先进方法的 6 到 17 倍，是 CGAL 算法的 419 倍。原则上，它可以直接用于计算曲线多边形的中轴线，与 Chin 的方法相比扩大了应用范围。

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引用次数: 0

3D data augmentation and dual-branch model for robust face forgery detection 三维数据增强和双分支模型鲁棒人脸伪造检测

IF 2.5 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Graphical Models

Pub Date : 2025-02-04 DOI: 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.

我们提出了双分支网络（DBNet），这是一种新的深度伪造检测框架，通过联合建模3D-temporal和细粒度纹理表示来解决现有工作的关键限制。具体来说，我们的目标是研究如何(1)在统一的模型中捕获动态属性和空间细节；(2)通过时间一致的建模来识别局部工件之外的细微不一致。为此，DBNet从视频中提取3D地标来构建RNN分支的时间序列，而Vision Transformer则分析局部补丁。引入了时间一致性感知损失来显式地监督RNN。此外，3D生成模型增强了训练数据。大量的实验表明，我们的方法在基准测试中达到了最先进的性能，消融研究证实了它在各种操作和压缩下推广到未见数据的有效性。

引用次数: 0

Efficient alternating and joint distance minimization methods for adaptive spline surface fitting 自适应样条曲面拟合的有效交替和接合距离最小化方法

IF 2.5 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Graphical Models

Pub Date : 2025-02-01 DOI: 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.

我们提出了一种基于参数化和自适应之间关键相互作用的自适应样条结构的分散数据拟合新范式。具体来说，我们引入了两种新的自适应拟合方案，将移动参数化与自适应样条细化相结合，用于从真实世界的散射点云中重建高精度CAD模型。第一种方案交替进行曲面拟合和数据参数优化。第二种方案对参数和表面控制点进行了联合优化。为了将所提出的拟合方法与自适应样条构造相结合，我们提出了边界点的关键处理方法。工业实例表明，在自适应样条近似框架内更新参数化，显着减少了达到一定精度所需的自由度，特别是当样条自适应由适当分级的分层网格驱动时。数值实验采用thb样条，从而在考虑的工业环境中利用现有的CAD集成，然而，任何自适应样条结构都可以选择。

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引用次数: 0

Discrete variable 3D models in Computer extended Descriptive Geometry (CeDG): Building of polygonal sheet-metal elbows and comparison against CAD 计算机扩展描述几何（CeDG）中的离散变量三维模型：多边形金属板弯头的建立及其与CAD的比较

IF 2.5 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Graphical Models

Pub Date : 2025-02-01 DOI: 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.

计算机扩展描述几何（CeDG）是一种基于描述几何的新方法，可以在动态几何软件工具提供的框架内构建3D模型。当连续参数发生变化时，可以交互式地探索参数CeDG模型，但对于离散参数则不是这样。这项研究展示了GeoGebra - CeDG方法的能力，该方法结合了建立具有动态参数化的离散变量3D模型的算法。基于新开发的CeDG算法，将几种3D模型及其扁平图案（中性纤维）与LogiTRACE v.14和Solid Edge 2024 （CAD）模型进行了比较。在几乎所有被定义为度量的维度上，CeDG模型的精度都超过了CAD模型。此外，CeDG方法是一种独特的方法，可以为任何套头数量的值提供自动解决方案。

引用次数: 0

Geometry of the visual cortex with applications to image inpainting and enhancement 视觉皮层的几何学及其在图像着色和增强中的应用

IF 2.5 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Graphical Models

Pub Date : 2025-02-01 DOI: 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.

在旋转翻译群SE(2)中加入受视觉皮层V1启发的亚黎曼结构，我们提出了基于准椭圆扩散的图像着色和增强算法。我们在Citti， Sarti和Boscain等人之前的方法实现上进行了创新，提出了一种替代方法，可以防止褪色，并且能够在我们称为WaxOn-WaxOff的过程中产生更清晰的结果。我们还利用亚黎曼结构使用SE(2)定义了一个全新的非锐化滤波器，类似于用于二维图像处理的经典非锐化滤波器。我们展示了我们的方法血管增强视网膜扫描。

引用次数: 0

Quasi-interpolation projectors for subdivision function spaces 细分函数空间的准插值投影

IF 2.5 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Graphical Models

Pub Date : 2025-02-01 DOI: 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.

细分曲面作为样条的延伸，在等几何分析中已成为求解复杂拓扑模型偏微分方程的一种有前途的技术。这激发了人们对通过细分函数空间来探索近似的兴趣。准插值是逼近领域的重要工具，具有计算费用低、数值稳定性强等优点。在本文中，我们提出了一种构造细分函数空间的拟插值投影的简单方法，该方法具有明确的公式并达到了非常理想的近似阶。基于细分掩码和极限位置掩码构造了局部插值问题，克服了细分基函数求值的繁琐和求显式解的困难。给出了环、修正环和Catmull-Clark细分的显式拟插值公式。数值实验表明，这些拟插值投影达到了预期的近似阶数，在等几何配置中具有良好的应用前景。

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引用次数: 0

Lightweight deep learning method for end-to-end point cloud registration 端到端点云配准的轻量级深度学习方法

IF 2.5 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Graphical Models

Pub Date : 2025-02-01 DOI: 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.

点云配准是计算机科学和人工智能领域的一项基础任务，它涉及到将不同角度的点云严格地转换成一个共同的坐标系。传统的配准方法往往缺乏鲁棒性，不能达到预期的精度水平。相比之下，基于深度学习的配准方法显示出更高的准确性和泛化性。然而，这些方法受到大参数大小、复杂网络架构以及与效率、鲁棒性和部分重叠相关的挑战的阻碍。在这项研究中，我们提出了一种轻量级的基于深度学习的配准方法，该方法从多个角度捕获特征，以预测重叠点并减轻非重叠点的干扰。具体来说，我们的方法利用修剪和权重共享量化技术来减小模型大小并简化网络结构。我们在来自ModelNet40数据集的噪声和部分重叠点云上评估了所提出的模型，并将其与其他现有方法的性能进行了比较。实验结果表明，该方法在不影响配准精度的前提下，显著减小了模型的参数大小。

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引用次数: 0

Strategies for reducing motion sickness in virtual reality through improved handheld controller movements 通过改进手持控制器运动来减少虚拟现实中的晕动病的策略

IF 2.5 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Graphical Models

Pub Date : 2025-01-28 DOI: 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.

随着技术的进步，用户对身临其境、真实的信息呈现的需求也在上升。传统的2D显示和交互无法满足现代标准，而虚拟现实（VR）因其沉浸式体验而受到关注。然而，使用控制器进行VR运动可能会由于视觉和前庭信号不匹配而导致头晕，从而影响VR体验。本文分析了vr引起眩晕的主要原因，并提出了改进的手持控制器运动策略。这些策略可以实时调整用户的俯仰角和视野，或者将用户在现实世界中的头部加速度映射到虚拟角色上。这些方法通过智能调节控制器到vr显示映射来减少眩晕。此外，本文还通过一系列实验验证了这些设计的实际效果，并对用户的眩晕程度进行了详细的数据分析。实验结果表明，采用特定改进的手持控制器运动设计可以显著提高用户在VR环境中的舒适度，有效减少眩晕和不适感的发生。

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引用次数: 0

HammingVis: A visual analytics approach for understanding erroneous outcomes of quantum computing in hamming space HammingVis：在汉明空间理解量子计算错误结果的可视化分析方法

IF 2.5 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Graphical Models

Pub Date : 2024-10-25 DOI: 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.

先进的量子计算机有能力进行实用的量子计算，以解决经典计算机难以解决的特定问题。然而，这些计算机容易受到噪声的影响，导致结果出现无法预期的错误，从而降低了它们的可信度。为了应对这一挑战，我们提出了 HammingVis，这是一种可视化分析方法，有助于识别和理解量子结果中的误差。鉴于这些误差在汉明空间中表现出潜在的结构模式，我们引入了两种图形可视化方法，从不同角度揭示这些模式。一种突出了误差的整体结构，另一种则侧重于重要子空间内误差的影响。我们进一步开发了一个原型系统，用于在汉明空间内交互式探索和辨别正确结果。我们提出了一种新颖的设计，用于区分错误结果和正确结果之间的邻域模式。我们通过涉及两种经典量子算法结果数据的案例研究，证明了我们方法的有效性。

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