Evaluating Situated Visualization in AR with Eye Tracking

TL;DR

This paper discusses the potential of using eye tracking to evaluate situated visualizations in augmented reality, highlighting challenges and opportunities for understanding user interaction in spatial contexts.

Contribution

It explores extending gaze-based evaluation methods to AR visualizations, proposing a new approach for assessing user perception and interaction.

Findings

Eye tracking offers valuable qualitative and quantitative insights.

Challenges include adapting evaluation methods to AR contexts.

Potential for new insights into user perception in AR environments.

Abstract

Augmented reality (AR) technology provides means for embedding visualization in a real-world context. Such techniques allow situated analyses of live data in their spatial domain. However, as existing techniques have to be adapted for this context and new approaches will be developed, the evaluation thereof poses new challenges for researchers. Apart from established performance measures, eye tracking has proven to be a valuable means to assess visualizations qualitatively and quantitatively. We discuss the challenges and opportunities of eye tracking for the evaluation of situated visualizations. We envision that an extension of gaze-based evaluation methodology into this field will provide new insights on how people perceive and interact with visualizations in augmented reality.