Gaze Self-Similarity Plot - A New Visualization Technique.

Area of Science:

• Human-Computer Interaction
• Cognitive Science
• Data Visualization

Background:

• Eye tracking is crucial for understanding human behavior through visual patterns.
• Traditional visualization methods like scan-paths and heat maps have limitations in capturing temporal eye movement dynamics.
• Effective presentation of eye tracking results is essential but challenging.

Purpose of the Study:

• To introduce a new visualization technique, the gaze self-similarity plot (GSSP).
• To address the limitations of existing methods in visualizing both spatial and temporal eye movement features.
• To demonstrate the utility of GSSP in analyzing complex eye movement data.

Main Methods:

• The proposed technique, gaze self-similarity plot (GSSP), is an extension of recurrence plots from time series analysis.
• GSSP visualizes spatial and temporal eye movement features on a single 2D plot.
• Two types of GSSP are presented to illustrate the approach.

Main Results:

• GSSP reveals previously hidden information in eye movement data by integrating spatial and temporal aspects.
• The technique offers a more comprehensive understanding of visual attention patterns.
• Examples demonstrate the types of insights obtainable through GSSP.

Conclusions:

• GSSP is a powerful tool for visualizing complex eye movement data.
• The technique enhances the analysis of human behavior based on visual patterns.
• GSSP has broad potential applications in various fields requiring eye movement analysis.