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
1. 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 --
2. 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 --
3. 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 --
4. 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 --
5. 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, transmogrification -- 5.4 Conclusion --
6. 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