检索结果-内蒙古大学图书馆

IEEE International Symposium on Mixed and Augmented Reality Workshops (ISMARW)

作者： Wolfgang Büschel Katja Krug Marc Satkowski Stefan Gumhold Raimund Dachselt Interactive Media Lab Dresden TUD Dresden University of Technology Chair of Computer Graphics and Visualization TUD Dresden University of Technology

ISBN: (数字)9798331506919

ISBN: (纸本)9798331506926

In this paper, we present a research platform to support studying collaboration in hybrid and co-located scenarios. Mixed-presence collaboration includes various novel and exciting use cases, such as situated and immersive data analysis by multiple users. However, research in this emerging field is hindered by the technical complexity of the setups and often requires re-implementation of common features. We address this issue by contributing a toolkit and research platform for mixed-presence collaboration that serves as an extensible baseline implementation and enables fast prototyping for user studies in collaborative mixed reality. Furthermore, our platform provides adjustable parameters, such as types of avatars, audio source placement, or the amount of simulated network latency. This way, developers are supported in making design choices regarding typical, re-occurring technical challenges.

关键词： Three-dimensional displays Data analysis Avatars Spatial audio Decision making Collaboration Mixed reality Complexity theory Synchronization Augmented reality

来源：评论

学校读者我要写书评

暂无评论

A Constructivism-based Approach to Treemap Literacy in the Classroom

A Constructivism-based Approach to Treemap Literacy in the C...

引用

44th Annual Conference on European Association for Computer graphics, EUROgraphics 2023

作者： Firat, Elif E. Lang, Colm Srinivas, Bhumika Peng, Ilena Laramee, Robert S. Joshi, Alark Department of Computer Engineering Cukurova University Turkey Visualization and Graphics Lab Department of Computer Science University of San Francisco CA United States School of Computer Science University of Nottingham United Kingdom

ISBN: (纸本)9783038682103

Treemaps are a popular representation to show hierarchical as well as part-to-whole relationships in data. While most students are aware of node-link representations/network diagrams based on their K-12 education, treemaps are often a novel representation to them. We present our experience of developing a software using principles from constructivism to help students understand treemaps using linked, side-by-side views of a node-link diagram and a treemap of the same data. Based on the qualitative survey conducted at the end of the intervention, students found the linked views to be beneficial for understanding hierarchical representation of data using treemaps. © 2023 The Authors.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Stereo Conversion with Disparity-Aware Warping, Compositing and Inpainting

Stereo Conversion with Disparity-Aware Warping, Compositing ...

引用

IEEE Workshop on Applications of Computer Vision (WACV)

作者： Lukas Mehl Andrés Bruhn Markus Gross Christopher Schroers Institute for Visualization and Interactive Systems University of Stuttgart Department of Computer Science Computer Graphics Lab ETH Zurich DisneyResearch|Studios Switzerland

Despite of exciting advances in image-based rendering and novel view synthesis, it is still challenging to achieve high-resolution results that can reach production-level quality when applying such methods to the task of stereo conversion. At the same time, only very few dedicated stereo conversion approaches exist, which also fall short in terms of the required quality. Hence, in this paper, we present a novel method for high-resolution 2D-to-3D conversion. It is fully differentiable in all of its stages and performs disparity-informed warping, consistent foreground-background compositing, and background-aware inpainting. To enable temporal consistency in the resulting video, we propose a strategy to integrate information from additional video frames. Extensive ablation studies validate our design choices, leading to a fully automatic model that outperforms existing approaches by a large margin (49-70% LPIPS error reduction). Finally, inspired from current practices in manual stereo conversion, we introduce optional interactive tools into our model, which allow to steer the conversion process and make it significantly more applicable for 3D film production.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Composition of Geospatial visualizations for Scale-aware Views of Multiple Outcome Variables in Population Surveys

Composition of Geospatial Visualizations for Scale-aware Vie...

引用

International Conference on Information Visualisation (IV)

作者： Harshitha Ravindra Jaya Sreevalsan-Nair Graphics-Visualization-Computing Lab IIIT Bangalore Bangalore India

ISBN: (纸本)9781665490085

Population survey data is important for understanding the status of well-being along any dimensions, i.e., social, economic, political, health, etc. This data generates spatial point patterns which can be explored and analyzed using visualization. Given the spatial aspect of the data, there is a requirement of using cartographic maps, which are mostly limited to visualizing a single variable in most cases. Here, it is also important that the choice of visualizations also enable scale-aware analysis when zooming in and out of the maps, since the data is from the smaller political units and can be aggregated to larger political units. Thus, we explore the different visual compositions which use mathematical operators and the composite layouts for visualizing multiple outcome variables in survey data. The mathematical operators allow the use of univariate and bivariate data modeling and representation, and composite layouts of interest are juxtaposition and superimposed views. We demonstrate the inferences from visualizations using a case study on malnutrition in children under five in India. Our work shows that a visual composition of binary relationships represented in a visualization and a juxtaposed layout of such pairwise variables is effective in making inferences from the multivariate spatial point patterns in population data.

关键词： Heating systems visualization Sociology Layout Data visualization Spatial databases Mathematical models

来源：评论

学校读者我要写书评

暂无评论

Understanding multi-modal brain network data: An immersive 3D visualization approach

引用

Computers and graphics (Pergamon) 2022年 106卷 88-97页

作者： Pester, Britta Russig, Benjamin Winke, Oliver Ligges, Carolin Dachselt, Raimund Gumhold, Stefan Chair for Computer Graphics and Visualization TU Dresden Germany Jena University Hospital Department of Child and Adolescent Psychiatry Psychosomatic Medicine and Psychotherapy Friedrich Schiller University Jena Germany Interactive Media Lab Dresden TU Dresden Germany TU Dresden Germany Germany

Understanding the human brain requires the incorporation of functional interaction patterns that depend on a variety of features like experimental setup, strength of directed connectedness or variability between several individuals or groups. In addition to these external factors, there are internal properties of the brain network as for example temporal propagation of connections, or connectivity patterns that only occur in a distinct frequency range of the signal. The visualization of detected networks covering all necessary information poses a substantial problem which is mainly due to the high number of features that have to be integrated within the same view in a natural spatial context. To address this problem, we propose a new tool that transfers the network into an anatomically arranged origin–destination view in a virtual visual analysis lab. This offers the user an opportunity to assess the temporal evolution of connectivity patterns and provides an intuitive and motivating way of exploring the corresponding features via navigation and interaction in virtual reality (VR). The approach was evaluated in a user study including participants with neuroscientific background as well as people working in the field of computer science. As a first proof of concept trial we used functional brain networks derived from time series of electroencephalography recordings evoked by visual stimuli. All participants gave a positive general feedback, notably they saw a benefit in using the VR view instead of the compared 2D desktop variant. This suggests that our application successfully fills a gap in the visualization of high-dimensional brain networks and that it is worthwhile to further follow and enhance the proposed representation method. © 2022 Elsevier Ltd

关键词： Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

CAP-DSDN: Node Co-association Prediction in Communities in Dynamic Sparse Directed Networks and a Case Study of Migration Flow 14

CAP-DSDN: Node Co-association Prediction in Communities in D...

引用

14th International Conference on Knowledge Discovery and Information Retrieval, KDIR 2022 as part of 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2022

作者： Sreevalsan-Nair, Jaya Jakher, Astha Graphics-Visualization-Computing Lab. International Institute of Information Technology Bangalore Bangalore India Department of Humanities and Social Sciences IIT Kharagpur West Bengal Kharagpur721302 India

ISBN: (纸本)9789897586149

Predicting the community structure in the time series, or snapshots, of a real-world graph in the future, is a pertinent challenge. This is motivated by the study of migration flow networks. The dataset is characterized by edge sparsity due to the inconsistent availability of data. Thus, we generalize the problem to predicting community structure in a dynamic sparse directed network (DSDN). We introduce a novel application of co-association which is a pairwise relationship between the nodes belonging to the same community. We thus propose a three-step algorithm, CAP-DSDN, for co-association prediction (CAP) in such a network. Given the absence of benchmark data or ground truth, we use an ensemble of community detection (CD) algorithms and evaluation metrics widely used for directed networks. We then define a metric based on entropy rate as a threshold to filter the network for determining a significant and data-complete subnetwork. We propose the use of autoregressive models for predicting the co-association relationship given in its matrix format. We demonstrate the effectiveness of our proposed method in a case study of international refugee migration during 2000–18. Our results show that our method works effectively for migration flow networks for short-term prediction and when the data is complete across all snapshots. Copyright © 2022 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

To the Point: From Dynamic Heatmap Video to Gaze Points 25

To the Point: From Dynamic Heatmap Video to Gaze Points

引用

Proceedings of the 2025 Symposium on Eye Tracking Research and Applications

作者： Beryl Gnanaraj Swetha Manivasagam Jaya Sreevalsan-Nair Graphics-Visualization-Computing Lab International Institute of Information Technology Bangalore Bangalore Karnataka India Department of Computer Science and Engineering PSG College of Technology Coimbatore Tamil Nadu India

来源：评论

学校读者我要写书评

暂无评论

Improving Uncertainty-Error Correspondence in Deep Bayesian Medical Image Segmentation

TechRxiv

引用

TechRxiv 2023年

作者： Mody, Prerak de Plaza, Nicolas Chaves Astrenidou, Eleftheria de Ridder, Mischa Hoekstra, Nienke Hildebrandt, Klaus Staring, Marius Radiology Leiden University Medical Center Netherlands The Department of Radiation Oncology Leiden University Medical Center Netherlands University Medical Center Utrecht Netherlands The Computer Graphics and Visualization Lab TU Delft Netherlands

Increased usage of automated tools like deep learning in medical image segmentation has alleviated the bottleneck of manual contouring. This has shifted manual labour to quality assessment (QA) of automated contours which involves detecting errors and correcting them. A potential solution to semi-automated QA is to use deep Bayesian uncertainty to recommend potentially erroneous regions, thus reducing time spent on error detection. Previous work has investigated the correspondence between uncertainty and error, however, no work has been done on improving the "utility" of Bayesian uncertainty maps such that it is only present in inaccurate regions and not in the accurate ones. Our work trains the FlipOut model with the Accuracy-vs-Uncertainty (AvU) loss which promotes uncertainty to be present only in inaccurate regions. We apply this method on datasets of two radiotherapy body sites, namely CT scans of head and neck and prostate MRs. Uncertainty heatmaps (i.e. predictive entropy) are evaluated using ROC and Precision-Recall curves. Numerical results show that when compared to the Bayesian baseline the proposed method successfully suppresses uncertainty for accurate voxels, with similar presence of uncertainty for inaccurate voxels. Code to reproduce experiments is available on https://***/prerakmody/ bayesuncertainty-error-correspondence. © 2023, CC BY.

关键词： Computerized tomography

来源：评论

学校读者我要写书评

暂无评论

PREVIS - A Combined Machine Learning and Visual Interpolation Approach for Interactive Reverse Engineering in Assembly Quality Control 15

PREVIS - A Combined Machine Learning and Visual Interpolatio...

引用

15th CIRP Conference on Intelligent Computation in Manufacturing Engineering, ICME 2021

作者： Ruediger, Patrick Claus, Felix Leonhardt, Viktor Hagen, Hans Aurich, Jan C. Garth, Christoph Technische Universität Kaiserslautern P. O. Box 3049 Kaiserslautern67653 Germany Computer Graphics and HCI Lab Technische Universität Kaiserslautern P. O. Box 3049 Kaiserslautern67653 Germany Scientific Visualization Lab Technische Universität Kaiserslautern P. O. Box 3049 Kaiserslautern67653 Germany

We present PREVIS, a visual analytics tool, enhancing machine learning performance analysis in engineering applications. The presented toolchain allows for a direct comparison of regression models. In addition, we provide a methodology to visualize the impact of regression errors on the underlying field of interest in the original domain, the part geometry, via exploiting standard interpolation methods. Further, we allow a real-time preview of user-driven parameter changes in the displacement field via visual interpolation. This allows for fast and accountable online change management. We demonstrate the effectiveness with an ex-ante optimization of an automotive engine hood. © 2022 Elsevier B.V.. All rights reserved.

关键词： Quality control

来源：评论

学校读者我要写书评

暂无评论

CV4FEE: Flood Extent Estimation Using Consensus Voting in Ensemble of Methods for Change Detection in Sentinel-1 GRD SAR Images

CV4FEE: Flood Extent Estimation Using Consensus Voting in En...

引用

Asian and Pacific Conference on Synthetic Aperture Radar (APSAR)

作者： Ragesh Thangavel Jaya Sreevalsan-Nair Center for Information Technology and Public Policy IIIT Bangalore Bangalore India Graphics-Visualization-Computing Lab IIIT Bangalore Bangalore India

ISBN: (纸本)9781728173344

There are several methods for finding flooded areas using change detection from C-band Sentinel-l temporal GRDH Synthetic Aperture Radar (SAR) images. Using these methods, an automatic flood extent mapping is obtained through differences between multiple time instances of SAR images, which itself is processed to remove noise and isolated pixels. While a few selected methods give comparable results using similar approaches, it is difficult to determine the best result amongst them. Hence, we propose CV4FEE, which is a consensus voting (CV) of outcomes from an ensemble of flood extent estimation (FEE) methods. We select three different state-of-the-art FEE methods, based on a specific criterion. We then use different consensus voting functions to compute deterministic as well as probabilistic flood extent maps, thus accounting for uncertainty in computation in selected methods. We demonstrate our results of flood area estimation in two different flooding events in India, namely the Hyderabad flood and the Nivar cyclone, in 2020. We show that the probabilistic maps give flood extent estimation that confirms the GEE4FLOOD results, qualitatively. Our method successfully demonstrates the uncertainty in the estimation process.

关键词： Uncertainty Systematics Estimation Lakes Probabilistic logic Reservoirs Radar polarimetry

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：