Open AccessBook
Image-Based Visualization: Interactive Multidimensional Data Exploration
Christophe Hurter
- 01 Dec 2015
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TL;DR: This book will show how to take advantage of graphic card computation power with techniques called GPGPUs (general-purpose computing on graphics processing units) to produce fast and efficient data visualization and interaction.
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Abstract: Our society has entered a data-driven era, one in which not only are enormous amounts of data being generated daily but there are also growing expectations placed on the analysis of this data. Some data have become simply too large to be displayed and some have too short a lifespan to be handled properly with classical visualization or analysis methods. In order to address these issues, this book explores the potential solutions where we not only visualize data, but also allow users to be able to interact with it. Therefore, this book will focus on two main topics: large dataset visualization and interaction. Graphic cards and their image processing power can leverage large data visualization but they can also be of great interest to support interaction. Therefore, this book will show how to take advantage of graphic card computation power with techniques called GPGPUs (general-purpose computing on graphics processing units). As specific examples, this book details GPGPU usages to produce fast enough visualization to be interactive with improved brushing techniques, fast animations between different data representations, and view simplifications (i.e. static and dynamic bundling techniques). Since data storage and memory limitation is less and less of an issue, we will also present techniques to reduce computation time by using memory as a new tool to solve computationally challenging problems. We will investigate innovative data processing techniques: while classical algorithms are expressed in data space (e.g. computation on geographic locations), we will express them in graphic space (e.g., raster map like a screen composed of pixels). This consists of two steps: (1) a data representation is built using straightforward visualization techniques; and (2) the resulting image undergoes purely graphical transformations using image processing techniques. This type of technique is called image-based visualization. The goal of this book is to explore new computing techniques using image-based techniques to provide efficient visualizations and user interfaces for the exploration of large datasets. This book concentrates on the areas of information visualization, visual analytics, computer graphics, and human-computer interaction. This book opens up a whole field of study, including the scientific validation of these techniques, their limitations, and their generalizations to different types of datasets.
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Citations
State of the Art in Edge and Trail Bundling Techniques
Antoine Lhuillier,Christophe Hurter,Alexandru Telea +2 more
- 01 Jun 2017
TL;DR: A data‐based taxonomy is proposed that organizes bundling methods on the type of data they work on (graphs vs trails), and a generic framework that describes the typical steps of all bundling algorithms in terms of high‐level operations is proposed.
A Survey of Information Visualization Books
Dylan Rees,Robert S. Laramee +1 more
TL;DR: This paper features a novel two‐level classification based on both books and chapter topics examined in each book, enabling the reader to quickly identify to what depth a topic of interest is covered within a particular book.
Geospatial Information Visualization and Extended Reality Displays
Arzu Çöltekin,Amy L. Griffin,Aidan Slingsby,Anthony C. Robinson,Sidonie Christophe,Victoria Rautenbach,Min Chen,Christopher Pettit,Alexander Klippel +8 more
- 01 Jan 2020
TL;DR: This chapter reviews and summarizes the current state of the art in geovisualization and extended reality, covering a wide range of approaches to these subjects in domains that are related to geographic information science, and introduces the spectrum of terminology on virtual, augmented and mixed reality.
P4: Portable Parallel Processing Pipelines for Interactive Information Visualization
Jianping Kelvin Li,Kwan-Liu Ma +1 more
TL;DR: P4 narrows the gap between expressiveness and scalability in information visualization toolkits by simplifying the development of GPU-accelerated visualization systems while supporting a high degree of flexibility and customization for design specification.
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Functional Decomposition for Bundled Simplification of Trail Sets
TL;DR: A new approach to bundling based on functional decomposition of the underling dataset is proposed, which recovers the functional nature of the curves by representing them as linear combinations of piecewise-polynomial basis functions with associated expansion coefficients.
References
Mean shift: a robust approach toward feature space analysis
Dorin Comaniciu,Peter Meer +1 more
TL;DR: It is proved the convergence of a recursive mean shift procedure to the nearest stationary point of the underlying density function and, thus, its utility in detecting the modes of the density.
12.9K
The eyes have it: a task by data type taxonomy for information visualizations
Ben Shneiderman
- 03 Sep 1996
TL;DR: A task by data type taxonomy with seven data types and seven tasks (overview, zoom, filter, details-on-demand, relate, history, and extracts) is offered.
The university of Florida sparse matrix collection
Timothy A. Davis,Yifan Hu +1 more
TL;DR: The University of Florida Sparse Matrix Collection, a large and actively growing set of sparse matrices that arise in real applications, is described and a new multilevel coarsening scheme is proposed to facilitate this task.
4.3K
Illumination for computer generated pictures
TL;DR: Human visual perception and the fundamental laws of optics are considered in the development of a shading rule that provides better quality and increased realism in generated images.
The rendering equation
James T. Kajiya
- 31 Aug 1986
TL;DR: An integral equation is presented which generalizes a variety of known rendering algorithms and a new form of variance reduction, called Hierarchical sampling, which may be an efficient new technique for a wide variety of monte carlo procedures.
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