Image-Based Visualization: Interactive Multidimensional Data Exploration (Synthesis Lectures on Visualization)

✍ Scribed by Christophe Hurter

• Publisher: Morgan & Claypool Publishers
• Tongue: English
• Leaves: 131
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Introduction
1.1 Image-based Visualization
    1.1.1   Definition
1.2 Image-based Algorithm Opportunities
1.3 The Information Visualization Pipeline and Its Extension
1.4 GPGPU Usages to Address Scalability Issues
    1.4.1   GP/GPU Technique and History
    1.4.2   Image-based and the Graphic Card
1.5 Data Types
    1.5.1   Time-Dependent Data
    1.5.2   Movement Data
    1.5.3   Graph Data
1.6 Book Roadmap
Motivating Example
2.1 Visualization Evaluation
2.2 Application Domain
    2.2.1   Instance of Design Evaluation: The Radar Comet
2.3 The Card and Mackinlay Model Improvements
2.4 Characterization or Data Exploration Tool
2.5 FromDaDy: From Data to Display
2.6 Conclusion
Data Density Maps
3.1 Kernel Density Estimation: An Image-based Technique
    3.1.1   GPU Implementation
3.2 Interaction Techniques
    3.2.1   Brushing Technique
    3.2.2   Brushing Technique with Density Maps
    3.2.3   Brushing Technique with 3D Volumes
    3.2.4   Interactive Lighting Direction
    3.2.5   Density Maps as Data Sources
3.3 Application Domains
    3.3.1   Pattern Detection
    3.3.2   Exploration of Aircraft Proximity
    3.3.3   Exploration of Gaze Recording
3.4 Conclusion
Edge Bundling
4.1 SBEB: Skeleton-based Edge Bundling
4.2 KDEEB: Kernel Density Edge Bundling
4.3 Dynamic KDEEB
4.4 3D DKEEB
4.5 Directional KDEEB
4.6 Edge Bundling Generalization
4.7 Density Compatibility
4.8 Proposal to Improve Bundling Techniques
4.9 Conclusion
Animation with Large Datasets
5.1 Animation between Dual Frames
    5.1.1   Rotation to Support Dual Scatterplot Layout
    5.1.2   Animation between an Image and its Histogram
    5.1.3   Interpolation between Two Views with Large Dataset
    5.1.4   The Animation as a Tool to Detect Outliers
5.2 Animated Particles
    5.2.1   Particle System Requirements
5.3 Distortions
    5.3.1   2D Lens Distortion
    5.3.2   3D Lens Distortion
    5.3.3   Bundled Distortion
    5.3.4   Obstacle Avoidance
    5.3.5   Casual Infovis: Free Distortion, Transpogrification
5.4 Conclusion
Research Outlook and Vision
6.1 Graphic Cards and Raster Map
    6.1.1   The Physics of Light is a Rendering Process with Modern Graphic Cards
    6.1.2   Data Exploration and Manipulation with Image-based Techniques
    6.1.3   Raster Data Inaccuracy
6.2 Future Challenges
    6.2.1   Edge Bundling
    6.2.2   Distortion: Point Cloud Display
6.3 Image-based Algorithm in Application Domains
    6.3.1   Eye Tracking
    6.3.2   Image Processing: Skin Cancer Investigation
    6.3.3   Cognitive Maps and Alzheimer Disease
6.4 Conclusion
Bibliography

Author Biography
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