Computers & Graphics-Uk最新文献

Retraction notice to “SHREC 2021: 3D point cloud change detection for street scenes” 《SHREC 2021：街景三维点云变化检测》撤回通知

IF 2.5 4区计算机科学

Computers & Graphics-Uk Pub Date : 2024-12-01 DOI: 10.1016/j.cag.2024.104127

Tao Ku , Sam Galanakis , Bas Boom , Remco C. Veltkamp , Darshan Bangera , Shankar Gangisetty , Nikolaos Stagakis , Gerasimos Arvanitis , Konstantinos Moustakas

引用次数: 0

Contrast and content preserving HDMR-based color-to-gray conversion 对比度和内容保持基于hdmr的彩色到灰色转换

IF 2.5 4区计算机科学

Computers & Graphics-Uk Pub Date : 2024-12-01 DOI: 10.1016/j.cag.2024.104110

Ayça Ceylan, Evrim Korkmaz Özay, Burcu Tunga

{"title":"Contrast and content preserving HDMR-based color-to-gray conversion","authors":"Ayça Ceylan, Evrim Korkmaz Özay, Burcu Tunga","doi":"10.1016/j.cag.2024.104110","DOIUrl":"10.1016/j.cag.2024.104110","url":null,"abstract":"<div><div>Converting a color image into a grayscale image is a complex problem that is based on preserving color contrast, sharpness, and luminance. In this paper, a novel image decolorization algorithm is proposed using High Dimensional Model Representation (HDMR) with an optimization procedure that retains color content and contrast. In the proposed algorithm, a color image is first decomposed into HDMR components and then the components are categorized depending on whether they are colored or colorless. After that, the image is reconstructed by merging the weighted colored and colorless HDMR components. The weight coefficients are determined by an optimization process. The proposed algorithm both visually and quantitatively compared with state-of-the-art methods in the literature using various performance evaluation metrics. As regards all obtained results, the HDMR based image decolorization algorithm is more potent and has better performance in overall comparison. Most importantly, this algorithm has a flexible structure as it is able to produce various grayscale images for different thresholds of visible color contrast which makes this algorithm superior given that it is the only one that accomplishes this feat in the literature to the best of our knowledge.</div></div>","PeriodicalId":50628,"journal":{"name":"Computers & Graphics-Uk","volume":"125 ","pages":"Article 104110"},"PeriodicalIF":2.5,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142746872","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}

引用次数: 0

Foreword to the special section on Conference on Graphics, Patterns, and Images (SIBGRAPI 2024) 关于图形、模式和图像会议（SIBGRAPI 2024）特别部分的前言

IF 2.5 4区计算机科学

Computers & Graphics-Uk Pub Date : 2024-11-28 DOI: 10.1016/j.cag.2024.104137

Rita Borgo, João Luiz Dihl Comba

引用次数: 0

The phantom effect in information visualization 信息可视化中的幻影效应

IF 2.5 4区计算机科学

Computers & Graphics-Uk Pub Date : 2024-11-21 DOI: 10.1016/j.cag.2024.104109

Carolina Pereira , Tomás Alves , Sandra Gama

{"title":"The phantom effect in information visualization","authors":"Carolina Pereira , Tomás Alves , Sandra Gama","doi":"10.1016/j.cag.2024.104109","DOIUrl":"10.1016/j.cag.2024.104109","url":null,"abstract":"<div><div>Recent research focuses on understanding what triggers cognitive biases and how to alleviate them in the context of visualization use. Given its role in decision-making in other research fields, the Phantom Effect may hold exciting prospects among known biases. The Phantom Effect belongs to the category of decoy effects, where the decoy is an optimal yet unavailable alternative. We conducted a hybrid design experiment (N=76) where participants performed decision tasks based on information represented in different visualization idioms and phantom alternative’s unavailability presentation delays. We measured participants’ perceptual speed and visual working memory to study their impact on the expression of the Phantom Effect. Results show that visualization usually triggers the Phantom Effect, but two-sided bar charts mitigate this bias more effectively. We also found that waiting until the participant decides before presenting the decoy as unavailable helps alleviate the Phantom Effect. Although we did not find measurable effects, results also suggest that visual working memory and visualization literacy play a role in bias susceptibility. Our findings extend prior research in visualization-based decoy effects. They are the first steps to understanding the role of individual differences in the susceptibility to cognitive bias in visualization contexts.</div></div>","PeriodicalId":50628,"journal":{"name":"Computers & Graphics-Uk","volume":"125 ","pages":"Article 104109"},"PeriodicalIF":2.5,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142699316","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}

引用次数: 0

Efficient inverse-kinematics solver for precise pose reconstruction of skinned 3D models 用于精确重建带皮肤三维模型姿态的高效逆运动学求解器

IF 2.5 4区计算机科学

Computers & Graphics-Uk Pub Date : 2024-11-20 DOI: 10.1016/j.cag.2024.104125

Daeun Kang, Hyunah Park, Taesoo Kwon

{"title":"Efficient inverse-kinematics solver for precise pose reconstruction of skinned 3D models","authors":"Daeun Kang, Hyunah Park, Taesoo Kwon","doi":"10.1016/j.cag.2024.104125","DOIUrl":"10.1016/j.cag.2024.104125","url":null,"abstract":"<div><div>We propose an accelerated inverse-kinematics (IK) solving method aimed at reconstructing the pose of a 3D model based on the positions of surface markers or feature points. The model encompasses a skeletal structure of joints and a triangular mesh constituting its external surface. A mesh-based IK solving method optimizes the joint configurations to achieve the desired surface pose, assuming that surface markers are attached to the joints using linear-blended skinning, and that the target positions for these surface markers are provided. In the conventional IK solving method, the final position of a given joint is determined by iteratively computing error gradients based on the target marker positions, typically implemented using a 3-nested loop structure. In this paper, we streamline the standard IK computation process by precomputing all redundant terms for future use, leading to a significant reduction in asymptotic time complexity. We experimentally show that our accelerated IK solving method exhibits increasingly superior performance gains as the number of markers increases. Our pose reconstruction tests show performance improvements ranging between 34% and three times compared to a highly optimized implementation of the conventional method.</div></div>","PeriodicalId":50628,"journal":{"name":"Computers & Graphics-Uk","volume":"125 ","pages":"Article 104125"},"PeriodicalIF":2.5,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142699328","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}

引用次数: 0

Swarm manipulation: An efficient and accurate technique for multi-object manipulation in virtual reality 蜂群操纵：在虚拟现实中高效、精确地操纵多物体的技术

IF 2.5 4区计算机科学

Computers & Graphics-Uk Pub Date : 2024-11-19 DOI: 10.1016/j.cag.2024.104113

Xiang Li , Jin-Du Wang , John J. Dudley , Per Ola Kristensson

{"title":"Swarm manipulation: An efficient and accurate technique for multi-object manipulation in virtual reality","authors":"Xiang Li , Jin-Du Wang , John J. Dudley , Per Ola Kristensson","doi":"10.1016/j.cag.2024.104113","DOIUrl":"10.1016/j.cag.2024.104113","url":null,"abstract":"<div><div>The theory of swarm control shows promise for controlling multiple objects, however, scalability is hindered by cost constraints, such as hardware and infrastructure. Virtual Reality (VR) can overcome these limitations, but research on swarm interaction in VR is limited. This paper introduces a novel swarm manipulation technique and compares it with two baseline techniques: Virtual Hand and Controller (ray-casting). We evaluated these techniques in a user study (<span><math><mi>N</mi></math></span> = 12) in three tasks (selection, rotation, and resizing) across five conditions. Our results indicate that swarm manipulation yielded superior performance, with significantly faster speeds in most conditions across the three tasks. It notably reduced resizing size deviations but introduced a trade-off between speed and accuracy in the rotation task. Additionally, we conducted a follow-up user study (<span><math><mi>N</mi></math></span> = 6) using swarm manipulation in two complex VR scenarios and obtained insights through semi-structured interviews, shedding light on optimized swarm control mechanisms and perceptual changes induced by this interaction paradigm. These results demonstrate the potential of the swarm manipulation technique to enhance the usability and user experience in VR compared to conventional manipulation techniques. In future studies, we aim to understand and improve swarm interaction via internal swarm particle cooperation.</div></div>","PeriodicalId":50628,"journal":{"name":"Computers & Graphics-Uk","volume":"125 ","pages":"Article 104113"},"PeriodicalIF":2.5,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142721450","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}

引用次数: 0

Me! Me! Me! Me! A study and comparison of ego network representations 我我！我！我自我网络表征的研究与比较

IF 2.5 4区计算机科学

Computers & Graphics-Uk Pub Date : 2024-11-15 DOI: 10.1016/j.cag.2024.104123

Henry Ehlers , Daniel Pahr , Velitchko Filipov , Hsiang-Yun Wu , Renata G. Raidou

{"title":"Me! Me! Me! Me! A study and comparison of ego network representations","authors":"Henry Ehlers , Daniel Pahr , Velitchko Filipov , Hsiang-Yun Wu , Renata G. Raidou","doi":"10.1016/j.cag.2024.104123","DOIUrl":"10.1016/j.cag.2024.104123","url":null,"abstract":"<div><div>From social networks to brain connectivity, ego networks are a simple yet powerful approach to visualizing parts of a larger graph, i.e. those related to a selected focal node — the so-called “ego”. While surveys and comparisons of general graph visualization approaches exist in the literature, we note (i) the many conflicting results of comparisons of adjacency matrices and node-link diagrams, thus motivating further study, as well as (ii) the absence of such systematic comparisons for ego networks specifically. In this paper, we propose the development of empirical recommendations for ego network visualization strategies. First, we survey the literature across application domains and collect examples of network visualizations to identify the most common visual encodings, namely straight-line, radial, and layered node-link diagrams, as well as adjacency matrices. These representations are then applied to a representative, intermediate-sized network and subsequently compared in a large-scale, crowd-sourced user study in a mixed-methods analysis setup to investigate their impact on both user experience and performance. Within the limits of this study, and contrary to previous comparative investigations of adjacency matrices and node-link diagrams (outside of ego networks specifically), <em>participants performed systematically worse when using adjacency matrices than those using node-link diagrammatic representations</em>. Similar to previous comparisons of different node-link diagrams, <em>we do not detect any notable differences in participant performance between the three node-link diagrams</em>. Lastly, our quantitative and qualitative results indicate that <em>participants found adjacency matrices harder to learn, use, and understand than node-link diagrams</em>. We conclude that in terms of both participant experience and performance, a layered node-link diagrammatic representation appears to be the most preferable for ego network visualization purposes.</div></div>","PeriodicalId":50628,"journal":{"name":"Computers & Graphics-Uk","volume":"125 ","pages":"Article 104123"},"PeriodicalIF":2.5,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142699327","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}

引用次数: 0

Enhancing Visual Analytics systems with guidance: A task-driven methodology 通过引导增强可视分析系统：任务驱动方法

IF 2.5 4区计算机科学

Computers & Graphics-Uk Pub Date : 2024-11-10 DOI: 10.1016/j.cag.2024.104121

Ignacio Pérez-Messina, Davide Ceneda, Silvia Miksch

引用次数: 0

Enhancing semantic mapping in text-to-image diffusion via Gather-and-Bind 通过聚合绑定增强文本到图像扩散中的语义映射

IF 2.5 4区计算机科学

Computers & Graphics-Uk Pub Date : 2024-11-07 DOI: 10.1016/j.cag.2024.104118

Huan Fu, Guoqing Cheng

{"title":"Enhancing semantic mapping in text-to-image diffusion via Gather-and-Bind","authors":"Huan Fu, Guoqing Cheng","doi":"10.1016/j.cag.2024.104118","DOIUrl":"10.1016/j.cag.2024.104118","url":null,"abstract":"<div><div>Text-to-image synthesis is a challenging task that aims to generate realistic and diverse images from natural language descriptions. However, existing text-to-image diffusion models (e.g., Stable Diffusion) sometimes fail to satisfy the semantic descriptions of the users, especially when the prompts contain multiple concepts or modifiers such as colors. By visualizing the cross-attention maps of the Stable Diffusion model during the denoising process, we find that one of the concepts has a very scattered attention map, which cannot form a whole and gradually gets ignored. Moreover, the attention maps of the modifiers are hard to overlap with the corresponding concepts, resulting in incorrect semantic mapping. To address this issue, we propose a Gather-and-Bind method that intervenes in the cross-attention maps during the denoising process to alleviate the catastrophic forgetting and attribute binding problems without any pre-training. Specifically, we first use information entropy to measure the dispersion degree of the cross-attention maps and construct an information entropy loss to gather these scattered attention maps, which eventually captures all the concepts in the generated output. Furthermore, we construct an attribute binding loss that minimizes the distance between the attention maps of the attributes and their corresponding concepts, which enables the model to establish correct semantic mapping and significantly improves the performance of the baseline model. We conduct extensive experiments on public datasets and demonstrate that our method can better capture the semantic information of the input prompts. Code is available at <span><span>https://github.com/huan085128/Gather-and-Bind</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":50628,"journal":{"name":"Computers & Graphics-Uk","volume":"125 ","pages":"Article 104118"},"PeriodicalIF":2.5,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142652456","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}

引用次数: 0

Learning geometric complexes for 3D shape classification 学习用于三维形状分类的几何复合物

IF 2.5 4区计算机科学

Computers & Graphics-Uk Pub Date : 2024-11-07 DOI: 10.1016/j.cag.2024.104119

Prachi Kudeshia, Muhammad Altaf Agowun, Jiju Poovvancheri

{"title":"Learning geometric complexes for 3D shape classification","authors":"Prachi Kudeshia, Muhammad Altaf Agowun, Jiju Poovvancheri","doi":"10.1016/j.cag.2024.104119","DOIUrl":"10.1016/j.cag.2024.104119","url":null,"abstract":"<div><div>Geometry and topology are vital elements in discerning and describing the shape of an object. Geometric complexes constructed on the point cloud of a 3D object capture the geometry as well as topological features of the underlying shape space. Leveraging this aspect of geometric complexes, we present an attention-based dual stream graph neural network (DS-GNN) for 3D shape classification. In the first stream of DS-GNN, we introduce spiked skeleton complex (SSC) for learning the shape patterns through comprehensive feature integration of the point cloud’s core structure. SSC is a novel and concise geometric complex comprising principal plane-based cluster centroids complemented with per-centroid spatial locality information. The second stream of DS-GNN consists of alpha complex which facilitates the learning of geometric patterns embedded in the object shapes via higher dimensional simplicial attention. To evaluate the model’s response to different shape topologies, we perform a persistent homology-based object segregation that groups the objects based on the underlying topological space characteristics quantified through the second Betti number. Our experimental study on benchmark datasets such as ModelNet40 and ScanObjectNN shows the potential of the proposed GNN for the classification of 3D shapes with different topologies and offers an alternative to the current evaluation practices in this domain.</div></div>","PeriodicalId":50628,"journal":{"name":"Computers & Graphics-Uk","volume":"125 ","pages":"Article 104119"},"PeriodicalIF":2.5,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142652033","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}

引用次数: 0