Computers & Graphics-Uk最新文献_第9页

TPVis: A visual analytics system for exploring test case prioritization methods TPVis：用于探索测试用例优先级排序方法的可视化分析系统

IF 2.5 4区计算机科学

Computers & Graphics-Uk Pub Date : 2024-09-05 DOI: 10.1016/j.cag.2024.104064

José Arthur Silveira , Leandro Vieira , Nivan Ferreira

{"title":"TPVis: A visual analytics system for exploring test case prioritization methods","authors":"José Arthur Silveira , Leandro Vieira , Nivan Ferreira","doi":"10.1016/j.cag.2024.104064","DOIUrl":"10.1016/j.cag.2024.104064","url":null,"abstract":"<div><p>Software testing is a vital tool to ensure the quality and trustworthiness of the pieces of software produced. Test suites are often large, which makes the process of testing software a costly and time-consuming process. In this context, test case prioritization (TCP) methods play an important role by ranking test cases in order to enable early fault detection and, hence, enable quicker problem fixes. The evaluation of such methods is a difficult problem, due to the variety of the methods and objectives. To address this issue, we present TPVis, a visual analytics framework that enables the evaluation and comparison of TCP methods designed in collaboration with experts in software testing. Our solution is an open-source web application that provides a variety of analytical tools to assist in the exploration of test suites and prioritization algorithms. Furthermore, TPVis also provides dashboard presets, that were validated with our domain collaborators, that support common analysis goals. We illustrate the usefulness of TPVis through a series of use cases that illustrate our system’s flexibility in addressing different problems in analyzing TCP methods. Finally, we also report on feedback received from the domain experts that indicate the effectiveness of TPVis. TPVis is available at <span><span>https://github.com/vixe-cin-ufpe/TPVis</span><svg><path></path></svg></span>.</p></div>","PeriodicalId":50628,"journal":{"name":"Computers & Graphics-Uk","volume":"124 ","pages":"Article 104064"},"PeriodicalIF":2.5,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142166763","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

Transferring transfer functions (TTF): A guided approach to transfer function optimization in volume visualization 传递函数（TTF）：体积可视化中转移函数优化的指导方法

IF 2.5 4区计算机科学

Computers & Graphics-Uk Pub Date : 2024-09-04 DOI: 10.1016/j.cag.2024.104067

Amin Nasim Saravi, Joshua Horacsek, Usman Alim, Julio Daniel Silva

{"title":"Transferring transfer functions (TTF): A guided approach to transfer function optimization in volume visualization","authors":"Amin Nasim Saravi, Joshua Horacsek, Usman Alim, Julio Daniel Silva","doi":"10.1016/j.cag.2024.104067","DOIUrl":"10.1016/j.cag.2024.104067","url":null,"abstract":"<div><p>In volume visualization, a transfer function tailored for one volume usually does not work for other similar volumes without careful tuning. This process can be tedious and time-consuming for a large set of volumes. In this work, we present a novel approach to transfer function optimization based on the differentiable volume rendering of a reference volume and its corresponding transfer function. Using two fully connected neural networks, our approach learns a continuous 2D separable transfer function that visualizes the features of interest with consistent visual properties between the volumes. Because many volume visualization software packages support separable transfer functions, users can export the optimized transfer function into a domain-specific application for further interactions. In tandem with domain experts’ input and assessments, we present two use cases to demonstrate the effectiveness of our approach. The first use case tracks the effect of an asteroid blast near the ocean surface. In this application, a volume and its corresponding transfer function seed our method, cascading transfer function optimization for the proceeding time steps. The second use case focuses on the visualization of white matter, gray matter, and cerebrospinal fluid in magnetic resonance imaging (MRI) volumes. We optimize an intensity-gradient transfer function for one volume from its segmentation. Then we use these results to visualize other brain volumes with different intensity ranges acquired on different MRI machines.</p></div>","PeriodicalId":50628,"journal":{"name":"Computers & Graphics-Uk","volume":"124 ","pages":"Article 104067"},"PeriodicalIF":2.5,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0097849324002024/pdfft?md5=a9712309d212a1aa1bbb843ba60a6d2c&pid=1-s2.0-S0097849324002024-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142229684","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

Empowering sign language communication: Integrating sentiment and semantics for facial expression synthesis 增强手语交流能力：整合情感和语义进行面部表情合成

IF 2.5 4区计算机科学

Computers & Graphics-Uk Pub Date : 2024-09-03 DOI: 10.1016/j.cag.2024.104065

Rafael V. Azevedo , Thiago M. Coutinho , João P. Ferreira , Thiago L. Gomes , Erickson R. Nascimento

{"title":"Empowering sign language communication: Integrating sentiment and semantics for facial expression synthesis","authors":"Rafael V. Azevedo , Thiago M. Coutinho , João P. Ferreira , Thiago L. Gomes , Erickson R. Nascimento","doi":"10.1016/j.cag.2024.104065","DOIUrl":"10.1016/j.cag.2024.104065","url":null,"abstract":"<div><p>Translating written sentences from oral languages to a sequence of manual and non-manual gestures plays a crucial role in building a more inclusive society for deaf and hard-of-hearing people. Facial expressions (non-manual), in particular, are responsible for encoding the grammar of the sentence to be spoken, applying punctuation, pronouns, or emphasizing signs. These non-manual gestures are closely related to the semantics of the sentence being spoken and also to the utterance of the speaker’s emotions. However, most Sign Language Production (SLP) approaches are centered on synthesizing manual gestures and do not focus on modeling the speaker’s expression. This paper introduces a new method focused in synthesizing facial expressions for sign language. Our goal is to improve sign language production by integrating sentiment information in facial expression generation. The approach leverages a sentence’s sentiment and semantic features to sample from a meaningful representation space, integrating the bias of the non-manual components into the sign language production process. To evaluate our method, we extend the Fréchet gesture distance (FGD) and propose a new metric called Fréchet Expression Distance (FED) and apply an extensive set of metrics to assess the quality of specific regions of the face. The experimental results showed that our method achieved state of the art, being superior to the competitors on How2Sign and PHOENIX14T datasets. Moreover, our architecture is based on a carefully designed graph pyramid that makes it simpler, easier to train, and capable of leveraging emotions to produce facial expressions. Our code and pretrained models will be available at: <span><span>https://github.com/verlab/empowering-sign-language</span><svg><path></path></svg></span>.</p></div>","PeriodicalId":50628,"journal":{"name":"Computers & Graphics-Uk","volume":"124 ","pages":"Article 104065"},"PeriodicalIF":2.5,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142173877","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

Human-in-the-loop: Using classifier decision boundary maps to improve pseudo labels 人在回路中：使用分类决策边界图改进伪标签

IF 2.5 4区计算机科学

Computers & Graphics-Uk Pub Date : 2024-08-30 DOI: 10.1016/j.cag.2024.104062

Bárbara C. Benato , Cristian Grosu , Alexandre X. Falcão , Alexandru C. Telea

{"title":"Human-in-the-loop: Using classifier decision boundary maps to improve pseudo labels","authors":"Bárbara C. Benato , Cristian Grosu , Alexandre X. Falcão , Alexandru C. Telea","doi":"10.1016/j.cag.2024.104062","DOIUrl":"10.1016/j.cag.2024.104062","url":null,"abstract":"<div><p>For classification tasks, several strategies aim to tackle the problem of not having sufficient labeled data, usually by automatic labeling or by fully passing this task to a user. Automatic labeling is simple to apply but can fail handling complex situations where human insights may be required to decide the correct labels. Conversely, manual labeling leverages the expertise of specialists but may waste precious effort which could be handled by automatic methods. More specifically, automatic solutions could be improved by combining an active learning loop with manual labeling assisted by visual depictions of a classifier’s behavior. We propose to include the human in the labeling loop by using manual labeling in feature spaces produced by a deep feature annotation (DeepFA) technique. To assist manual labeling, we provide users with visual insights on the classifier’s decision boundaries. Finally, we use the manual and automatically computed labels jointly to retrain the classifier in an active learning (AL) loop scheme. Experiments using a toy and a real-world application dataset show that our proposed combination of manual labeling supported by visualization of decision boundaries and automatic labeling can yield a significant increase in classifier performance with a quite limited user effort.</p></div>","PeriodicalId":50628,"journal":{"name":"Computers & Graphics-Uk","volume":"124 ","pages":"Article 104062"},"PeriodicalIF":2.5,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142150523","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

SingVisio: Visual analytics of diffusion model for singing voice conversion SingVisio：歌声转换扩散模型的可视化分析

IF 2.5 4区计算机科学

Computers & Graphics-Uk Pub Date : 2024-08-30 DOI: 10.1016/j.cag.2024.104058

Liumeng Xue , Chaoren Wang , Mingxuan Wang , Xueyao Zhang , Jun Han , Zhizheng Wu

引用次数: 0

Virtual reality inspection of chromatin 3D and 2D data 染色质三维和二维数据的虚拟现实检测

IF 2.5 4区计算机科学

Computers & Graphics-Uk Pub Date : 2024-08-30 DOI: 10.1016/j.cag.2024.104059

Elena Molina , David Kouřil , Tobias Isenberg , Barbora Kozlíková , Pere-Pau Vázquez

{"title":"Virtual reality inspection of chromatin 3D and 2D data","authors":"Elena Molina , David Kouřil , Tobias Isenberg , Barbora Kozlíková , Pere-Pau Vázquez","doi":"10.1016/j.cag.2024.104059","DOIUrl":"10.1016/j.cag.2024.104059","url":null,"abstract":"<div><p>Understanding the packing of long DNA strands into chromatin is one of the ultimate challenges in genomic research. An intrinsic part of this complex problem is studying the chromatin’s spatial structure. Biologists reconstruct 3D models of chromatin from experimental data, yet the exploration and analysis of such 3D structures is limited in existing genomic data visualization tools. To improve this situation, we investigated the current options of immersive methods and designed a prototypical VR visualization tool for 3D chromatin models that leverages virtual reality to deal with the spatial data. We showcase the tool in three primary use cases. First, we provide an overall 3D shape overview of the chromatin to facilitate the identification of regions of interest and the selection for further investigation. Second, we include the option to export the selected regions and elements in the BED format, which can be loaded into common analytical tools. Third, we integrate epigenetic modification data along the sequence that influence gene expression, either as in-world 2D charts or overlaid on the 3D structure itself. We developed our application in collaboration with two domain experts and gathered insights from two informal studies with five other experts.</p></div>","PeriodicalId":50628,"journal":{"name":"Computers & Graphics-Uk","volume":"124 ","pages":"Article 104059"},"PeriodicalIF":2.5,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0097849324001948/pdfft?md5=f80ba96ee4f32f07bbbc948215d8362d&pid=1-s2.0-S0097849324001948-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142136914","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

Advanced visualization of aortic dissection anatomy and hemodynamics 主动脉夹层解剖和血流动力学高级可视化

IF 2.5 4区计算机科学

Computers & Graphics-Uk Pub Date : 2024-08-30 DOI: 10.1016/j.cag.2024.104060

Aaron Schroeder , Kai Ostendorf , Kathrin Bäumler , Domenico Mastrodicasa , Veit Sandfort , Dominik Fleischmann , Bernhard Preim , Gabriel Mistelbauer

{"title":"Advanced visualization of aortic dissection anatomy and hemodynamics","authors":"Aaron Schroeder , Kai Ostendorf , Kathrin Bäumler , Domenico Mastrodicasa , Veit Sandfort , Dominik Fleischmann , Bernhard Preim , Gabriel Mistelbauer","doi":"10.1016/j.cag.2024.104060","DOIUrl":"10.1016/j.cag.2024.104060","url":null,"abstract":"<div><p>Aortic dissection is a life-threatening cardiovascular disease constituted by the delamination of the aortic wall. Due to the weakened structure of the false lumen, the aorta often dilates over time, which can – after certain diameter thresholds are reached – increase the risk of fatal aortic rupture. The identification of patients with a high risk of late adverse events is an ongoing clinical challenge, further complicated by the complex dissection anatomy and the wide variety among patients. Moreover, patient-specific risk stratification depends not only on morphological, but also on hemodynamic factors, which can be derived from computer simulations or 4D flow magnetic resonance imaging (MRI). However, comprehensible visualizations that depict the complex anatomical and functional information in a single view are yet to be developed. These visualization tools will assist clinical research and decision-making by facilitating a comprehensive understanding of the aortic state. For that purpose, we identified several visualization tasks and requirements in close collaboration with cardiovascular imaging scientists and radiologists. We displayed true and false lumen hemodynamics using pathlines as well as surface hemodynamics on the dissection flap and the inner vessel wall. Pathlines indicate antegrade and retrograde flow, blood flow through fenestrations, and branch vessel supply. Dissection-specific hemodynamic measures, such as interluminal pressure difference and flap compliance, provide further insight of the blood flow throughout the cardiac cycle. Finally, we evaluated our visualization techniques with cardiothoracic and vascular surgeons in two separate virtual sessions.</p></div>","PeriodicalId":50628,"journal":{"name":"Computers & Graphics-Uk","volume":"124 ","pages":"Article 104060"},"PeriodicalIF":2.5,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S009784932400195X/pdfft?md5=0ad3789d79a9874f94f737d74b5f7695&pid=1-s2.0-S009784932400195X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142136915","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

Interactive data comics for communicating medical data to the general public: A study of engagement and ease of understanding 向大众传播医学数据的交互式数据漫画：关于参与度和易理解性的研究

IF 2.5 4区计算机科学

Computers & Graphics-Uk Pub Date : 2024-08-29 DOI: 10.1016/j.cag.2024.104055

Melissa Fogwill, Areti Manataki

引用次数: 0

EasySkinning: Target-oriented skinning by mesh contraction and curve editing EasySkinning：通过网格收缩和曲线编辑实现面向目标的皮肤绘制

IF 2.5 4区计算机科学

Computers & Graphics-Uk Pub Date : 2024-08-29 DOI: 10.1016/j.cag.2024.104049

Jing Ma , Jituo Li , Dongliang Zhang

{"title":"EasySkinning: Target-oriented skinning by mesh contraction and curve editing","authors":"Jing Ma , Jituo Li , Dongliang Zhang","doi":"10.1016/j.cag.2024.104049","DOIUrl":"10.1016/j.cag.2024.104049","url":null,"abstract":"<div><p>Skinning, a critical process in animation that defines how bones influence the vertices of a 3D character model, significantly impacts the visual effect in animation production. Traditional methods are time-intensive and skill-dependent, whereas automatic techniques lack in flexibility and quality. Our research introduces EasySkinning, a user-friendly system applicable to complex meshes. This method comprises three key components: rigid weight initialization through Voronoi contraction, precise weight editing via curve tools, and smooth weight solving for reconstructing target deformations. EasySkinning begins by contracting the input mesh inwards to the skeletal bones, which improves vertex-to-bone mappings, particularly in intricate mesh areas. We also design intuitive curve-editing tools, allowing users to define more precise bone influential regions. The final stage employs advanced deformation algorithms for smooth weight solving, crucial for achieving desired animations. Through extensive experiments, we demonstrate that EasySkinning not only simplifies the creation of high-quality skinning weights but also consistently outperforms existing automatic and interactive skinning methods.</p></div>","PeriodicalId":50628,"journal":{"name":"Computers & Graphics-Uk","volume":"124 ","pages":"Article 104049"},"PeriodicalIF":2.5,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142150524","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

HiSEG: Human assisted instance segmentation HiSEG：人工辅助实例分割

IF 2.5 4区计算机科学

Computers & Graphics-Uk Pub Date : 2024-08-26 DOI: 10.1016/j.cag.2024.104061

Muhammed Korkmaz, T. Metin Sezgin

{"title":"HiSEG: Human assisted instance segmentation","authors":"Muhammed Korkmaz, T. Metin Sezgin","doi":"10.1016/j.cag.2024.104061","DOIUrl":"10.1016/j.cag.2024.104061","url":null,"abstract":"<div><p>Instance segmentation is a form of image detection which has a range of applications, such as object refinement, medical image analysis, and image/video editing, all of which demand a high degree of accuracy. However, this precision is often beyond the reach of what even state-of-the-art, fully automated instance segmentation algorithms can deliver. The performance gap becomes particularly prohibitive for small and complex objects. Practitioners typically resort to fully manual annotation, which can be a laborious process. In order to overcome this problem, we propose a novel approach to enable more precise predictions and generate higher-quality segmentation masks for high-curvature, complex and small-scale objects. Our human-assisted segmentation method, HiSEG, augments the existing Strong Mask R-CNN network to incorporate human-specified partial boundaries. We also present a dataset of hand-drawn partial object boundaries, which we refer to as “human attention maps”. In addition, the Partial Sketch Object Boundaries (PSOB) dataset contains hand-drawn partial object boundaries which represent curvatures of an object’s ground truth mask with several pixels. Through extensive evaluation using the PSOB dataset, we show that HiSEG outperforms state-of-the art methods such as Mask R-CNN, Strong Mask R-CNN, Mask2Former, and Segment Anything, achieving respective increases of +42.0, +34.9, +29.9, and +13.4 points in AP<span><math><msub><mrow></mrow><mrow><mtext>Mask</mtext></mrow></msub></math></span> metrics for these four models. We hope that our novel approach will set a baseline for future human-aided deep learning models by combining fully automated and interactive instance segmentation architectures.</p></div>","PeriodicalId":50628,"journal":{"name":"Computers & Graphics-Uk","volume":"124 ","pages":"Article 104061"},"PeriodicalIF":2.5,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142099001","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