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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.
These proceedings include the contributions to the 9th International Workshop on Vision, Modeling and Visualization held in November, 2004 in Stanford, USA. The contributions cover the areas: .Calibration, Registration, Tracking .Image and Video-based Modeling and Rendering .Simulation and Rendering .Geometry Processing .Volume Data Processing and Scientific Visualization The workshop has been organized jointly by members of the Computer Graphics Group at the Max-Planck-Institute in Saarbrücken and by members of Stanford University. VMV 2004 marks the launch of the Max Planck Center for Visual Computing and Communication between Stanford and the German Max Planck Society this year, which opens a new chapter of transatlantic research collaboration in this area. Additionally, VMV 2004 has generously been supported by the Graduate Research Center - 3D Image Analysis and Synthesis, Signal Processing Society IEEE, Sonderforschungsbereich 603, German Informatics Society GI and the Eurographics - European Association for Computer Graphics.
Vision, modeling, and visualization are complementary disciplines that are rapidly converging. This text presents papers about segmentation and feature extraction, image understanding, models from video, image fusion and direct volume rendering.
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 the fourth Workshop on Topology-Based Methods in Data Analysis and Visualization, TopoInVis 2011, held in Zurich, Switzerland. The workshop brought together many of the leading lights in the field for a mixture of formal presentations and discussion. One topic currently generating a great deal of interest, and explored in several chapters here, is the search for topological structures in time-dependent flows, and their relationship with Lagrangian coherent structures. Contributors also focus on discrete topologies of scalar and vector fields, and on persistence-based simplification, among other issues of note. The new research results included in this volume relate to all three key areas in data analysis—theory, algorithms and applications.
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.
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.
With a lot of recent developments in the field, this much-needed book has come at just the right time. It covers a variety of topics related to preserving and enhancing shape information at a geometric level. The contributors also cover subjects that are relevant to effectively capturing the structure of a shape by identifying relevant shape components and their mutual relationships.
Three dimensional modeling and visualization of environments is an increasingly important problem. This work addresses the problem of automatic 3D reconstruction and we present a system for unsupervised reconstruction of textured 3D models in the context of modeling indoor environments. We present solutions to all aspects of the modeling process and an integrated system for the automatic creation of large scale 3D models.