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Topological Methods in Data Analysis and Visualization II
When scientists analyze datasets in a search for underlying phenomena, patterns or causal factors, their first step is often an automatic or semi-automatic search for structures in the data. Of these feature-extraction methods, topological ones stand out due to their solid mathematical foundation. Topologically defined structures—as found in scalar, vector and tensor fields—have proven their merit in a wide range of scientific domains, and scientists have found them to be revealing in subjects such as physics, engineering, and medicine. Full of state-of-the-art research and contemporary hot topics in the subject, this volume is a selection of peer-reviewed papers originally presented at ...
Scientific Visualization: The Visual Extraction of Knowledge from Data
One of the greatest scientific challenges of the 21st century is how to master, organize and extract useful knowledge from the overwhelming flow of information made available by today’s data acquisition systems and computing resources. Visualization is the premium means of taking up this challenge. This book is based on selected lectures given by leading experts in scientific visualization during a workshop held at Schloss Dagstuhl, Germany. Topics include user issues in visualization, large data visualization, unstructured mesh processing for visualization, volumetric visualization, flow visualization, medical visualization and visualization systems. The book contains more than 350 color illustrations.
Topological Methods in Data Analysis and Visualization
Topology-based methods are of increasing importance in the analysis and visualization of datasets from a wide variety of scientific domains such as biology, physics, engineering, and medicine. Current challenges of topology-based techniques include the management of time-dependent data, the representation of large and complex datasets, the characterization of noise and uncertainty, the effective integration of numerical methods with robust combinatorial algorithms, etc. . The editors have brought together the most prominent and best recognized researchers in the field of topology-based data analysis and visualization for a joint discussion and scientific exchange of the latest results in the field. This book contains the best 20 peer-reviewed papers resulting from the discussions and presentations at the third workshop on "Topological Methods in Data Analysis and Visualization", held 2009 in Snowbird, Utah, US. The 2009 "TopoInVis" workshop follows the two successful workshops in 2005 (Slovakia) and 2007 (Germany).
GPU-Based Interactive Visualization Techniques
This book presents efficient visualization techniques, a prerequisite for the interactive exploration of complex data sets. High performance is demonstrated as a process of devising algorithms for the fast graphics processing units (GPUs) of modern graphics hardware. Coverage includes parallelization on cluster computers with several GPUs, adaptive rendering methods, and non-photorealistic rendering techniques for visualization.
Topology-based Methods in Visualization
This book presents 13 peer-reviewed papers as written results from the 2005 workshop "Topology-Based Methods in Visualization" that was initiated to enable additional stimulation in this field. It contains a survey of the state-of-the-art, as well original work by leading experts that has not been published before, spanning both theory and applications. It captures key concepts and novel ideas and serves as an overview of current trends in its subject.
Human Factors in Computing and Informatics
This book constitutes the refereed proceedings of the First International Conference on Human Factors in Computing and Informatics, SouthCHI 2013, held in Maribor, Slovenia, in July 2013. SouthCHI is the successor of the USAB Conference series and promotes all aspects of human-computer interaction. The 38 revised full papers presented together with 12 short papers, 4 posters and 3 doctoral thesis papers were carefully reviewed and selected from 169 submissions. The papers are organized in the following topical sections: measurement and usability evaluation; usability evaluation - medical environments; accessibility methodologies; game-based methodologies; Web-based systems and attribution research; virtual environments; design culture for ageing well: designing for "situated elderliness"; input devices; adaptive systems and intelligent agents; and assessing the state of HCI research and practice in South-Eastern Europe.
Foundations of Data Visualization
This is the first book that focuses entirely on the fundamental questions in visualization. Unlike other existing books in the field, it contains discussions that go far beyond individual visual representations and individual visualization algorithms. It offers a collection of investigative discourses that probe these questions from different perspectives, including concepts that help frame these questions and their potential answers, mathematical methods that underpin the scientific reasoning of these questions, empirical methods that facilitate the validation and falsification of potential answers, and case studies that stimulate hypotheses about potential answers while providing practical...
Real-Time Volume Graphics
Based on course notes of SIGGRAPH course teaching techniques for real-time rendering of volumetric data and effects; covers both applications in scientific visualization and real-time rendering. Starts with the basics (texture-based ray casting) and then improves and expands the algorithms incrementally. Book includes source code, algorithms, diagr
Vision, Modeling, and Visualization 2006
Summary: "These proceedings include the contributions to the 11th international Workshop Vision, Modeling, and Visualization 2006 held in Aachen, Germany. The papers cover the following topics: Image-based Reconstruction -- Textures and Rendering -- GPU-Programming -- Simulation and Visualization -- Image Processing -- Volume Visualization -- Geometry Processing and Rendering."--Publisher description.
Linked Data Visualization
Linked Data (LD) is a well-established standard for publishing and managing structured information on the Web, gathering and bridging together knowledge from different scientific and commercial domains. The development of Linked Data Visualization techniques and tools has been followed as the primary means for the analysis of this vast amount of information by data scientists, domain experts, business users, and citizens. This book covers a wide spectrum of visualization issues, providing an overview of the recent advances in this area, focusing on techniques, tools, and use cases of visualization and visual analysis of LD. It presents the basic concepts related to data visualization and the...
