Eye Tracking and Visual Analytics.

• Author: Burch, Michael.
• Place / Publishing House: Aalborg : : River Publishers,, 2021.; Ã2021.
• Year of Publication: 2021
• Edition: 1st ed.
• Language: English
• Physical Description: 1 online resource (382 pages)

Table of Contents

Front Cover -- Eye Tracking and Visual Analytics -- Contents -- Preface -- List of Figures -- List of Tables -- List of Abbreviations -- 1 Introduction -- 1.1 Tasks, Hypotheses, and Human Observers -- 1.2 Synergy Effects -- 1.3 Dynamic Visual Analytics -- 2 Visualization -- 2.1 Motivating Examples -- 2.2 Historical Background -- 2.2.1 Early Forms of Visualizations -- 2.2.2 The Age of Cartographic Maps -- 2.2.3 Visualization During Industrialization -- 2.2.4 After the Invention of the Computer -- 2.2.5 Visualization Today -- 2.3 Data Types and Visual Encodings -- 2.3.1 Primitive Data -- 2.3.2 Complex Data -- 2.3.3 Mixture of Data -- 2.3.4 Dynamic Data -- 2.3.5 Metadata -- 2.4 Interaction Techniques -- 2.4.1 Interaction Categories -- 2.4.2 Physical Devices -- 2.4.3 Users-in-the-Loop -- 2.5 Design Principles -- 2.5.1 Visual Enhancements and Decorations -- 2.5.2 Visual Structuring and Organization -- 2.5.3 General Design Flaws -- 2.5.4 Gestalt Laws -- 2.5.5 Optical Illusions -- 3 Visual Analytics -- 3.1 Key Concepts -- 3.1.1 Origin and First Stages -- 3.1.2 Data Handling and Management -- 3.1.3 System Ingredients Around the Data -- 3.1.4 Involved Research Fields and Future Perspectives -- 3.2 Visual Analytics Pipeline -- 3.2.1 Data Basis and Runtimes -- 3.2.2 Patterns, Correlations, and Rules -- 3.2.3 Tasks and Hypotheses -- 3.2.4 Refinements and Adaptations -- 3.2.5 Insights and Knowledge -- 3.3 Challenges of Algorithmic Concepts -- 3.3.1 Algorithm Classes -- 3.3.2 Parameter Specifications -- 3.3.3 Algorithmic Runtime Complexities -- 3.3.4 Performance Evaluation -- 3.3.5 Insights into the Running Algorithm -- 3.4 Applications -- 3.4.1 Dynamic Graphs -- 3.4.2 Digital and Computational Pathology -- 3.4.3 Malware Analysis -- 3.4.4 Video Data Analysis -- 3.4.5 Eye Movement Data -- 4 User Evaluation -- 4.1 Study Types -- 4.1.1 Pilot vs. Real Study.

4.1.2 Quantitative vs. Qualitative -- 4.1.3 Controlled vs. Uncontrolled -- 4.1.4 Expert vs. Non-Expert -- 4.1.5 Short-term vs. Longitudinal -- 4.1.6 Limited-number Population vs. Crowdsourcing -- 4.1.7 Field vs. Lab -- 4.1.8 With vs. Without Eye Tracking -- 4.2 Human Users -- 4.2.1 Level of Expertise -- 4.2.2 Age Groups -- 4.2.3 Cultural Differences -- 4.2.4 Vision Deficiencies -- 4.2.5 Ethical Guidelines -- 4.3 Study Design and Ingredients -- 4.3.1 Hypotheses and Research Questions -- 4.3.2 Visual Stimuli -- 4.3.3 Tasks -- 4.3.4 Independent and Dependent Variables -- 4.3.5 Experimenter -- 4.4 Statistical Evaluation and Visual Results -- 4.4.1 Data Preparation and Descriptive Statistics -- 4.4.2 Statistical Tests and Inferential Statistics -- 4.4.3 Visual Representation of the Study Results -- 4.5 Example User Studies Without Eye Tracking -- 4.5.1 Hierarchy Visualization Studies -- 4.5.2 Graph Visualization Studies -- 4.5.3 Interaction Technique Studies -- 4.5.4 Visual Analytics Studies -- 5 Eye Tracking -- 5.1 The Eye -- 5.1.1 Eye Anatomy -- 5.1.2 Eye Movement and Smooth Pursuit -- 5.1.3 Disorders and Diseases Influencing Eye Tracking -- 5.1.4 Corrected-to-Normal Vision -- 5.2 Eye Tracking History -- 5.2.1 The Early Days -- 5.2.2 Progress in the Field -- 5.2.3 Eye Tracking Today -- 5.2.4 Companies, Technologies, and Devices -- 5.2.5 Application Fields -- 5.3 Eye Tracking Data Properties -- 5.3.1 Visual Stimuli -- 5.3.2 Gaze Points, Fixations, Saccades, and Scanpaths -- 5.3.3 Areas of Interest (AOIs) and Transitions -- 5.3.4 Physiological and Additional Measures -- 5.3.5 Derived Metrics -- 5.4 Examples of Eye Tracking Studies -- 5.4.1 Eye Tracking for Static Visualizations -- 5.4.2 Eye Tracking for Interaction Techniques -- 5.4.3 Eye Tracking for Text/Label/Code Reading -- 5.4.4 Eye Tracking for User Interfaces.

5.4.5 Eye Tracking for Visual Analytics -- 6 Eye Tracking Data Analytics -- 6.1 Data Preparation -- 6.1.1 Data Collection and Acquisition -- 6.1.2 Organization and Relevance -- 6.1.3 Data Annotation and Anonymization -- 6.1.4 Data Interpretation -- 6.1.5 Data Linking -- 6.2 Data Storage, Adaptation, and Transformation -- 6.2.1 Data Storage -- 6.2.2 Validation, Verification, and Cleaning -- 6.2.3 Data Enhancement and Enrichment -- 6.2.4 Data Transformation -- 6.3 Algorithmic Analyses -- 6.3.1 Ordering and Sorting -- 6.3.2 Data Clustering -- 6.3.3 Summarization, Classing, and Classification -- 6.3.4 Normalization and Aggregation -- 6.3.5 Projection and Dimensionality Reduction -- 6.3.6 Correlation and Trend Analysis -- 6.3.7 Pairwise or Multiple Sequence Alignment -- 6.3.8 Artificial Intelligence-Related Approaches -- 6.4 Visualization Techniques and Visual Analytics -- 6.4.1 Statistical Plots -- 6.4.2 Point-based Visualization Techniques -- 6.4.3 AOI-based Visualization Techniques -- 6.4.4 Eye Tracking Visual Analytics -- 7 Open Challenges, Problems, and Difficulties -- 7.1 Eye Tracking Challenges -- 7.2 Eye Tracking Visual Analytics Challenges -- References -- Index -- About the Author -- Back Cover.