# Deadeye Visualization Revisited: Investigation of Preattentiveness and Applicability in Virtual Environments

## TL;DR

This paper investigates the Deadeye highlighting technique in 3D virtual environments, evaluating its effectiveness and robustness in VR, and exploring its application in volume rendering with user feedback.

## Contribution

It extends Deadeye's application from 2D to 3D visualizations, providing quantitative evaluation and practical insights for VR scenarios.

## Key findings

- Deadeye maintains high accuracy (>90%) in 3D VR with distractors.
- The technique effectively suppresses binocular disparities for target highlighting.
- User survey indicates benefits and limitations in VR volume rendering.

## Abstract

Visualizations rely on highlighting to attract and guide our attention. To make an object of interest stand out independently from a number of distractors, the underlying visual cue, e.g., color, has to be preattentive. In our prior work, we introduced Deadeye as an instantly recognizable highlighting technique that works by rendering the target object for one eye only. In contrast to prior approaches, Deadeye excels by not modifying any visual properties of the target. However, in the case of 2D visualizations, the method requires an additional setup to allow dichoptic presentation, which is a considerable drawback. As a follow-up to requests from the community, this paper explores Deadeye as a highlighting technique for 3D visualizations, because such stereoscopic scenarios support dichoptic presentation out of the box. Deadeye suppresses binocular disparities for the target object, so we cannot assume the applicability of our technique as a given fact. With this motivation, the paper presents quantitative evaluations of Deadeye in VR, including configurations with multiple heterogeneous distractors as an important robustness challenge. After confirming the preserved preattentiveness (all average accuracies above 90 %) under such real-world conditions, we explore VR volume rendering as an example application scenario for Deadeye. We depict a possible workflow for integrating our technique, conduct an exploratory survey to demonstrate benefits and limitations, and finally provide related design implications.