Locatability and Locatability Robustness of Visual Variables in Single Target Localization

2026-01-27

AI Summary

This study addresses the critical challenge of rapidly locating specific targets in complex visualizations—a fundamental problem in human-computer interaction. Through a large-scale user experiment, it systematically evaluates the efficiency of common visual variables, such as color and size, in single-target localization tasks, offering the first empirically grounded performance comparison within the visualization literature. Introducing the concept of “localization robustness” and integrating eye-tracking and response time data, the research reveals that all visual variables are adversely affected by the number of distractors in displays containing hundreds of objects, thereby challenging the prevailing assumption of preattentive pop-out. The findings demonstrate significant differences in robustness across visual variables under varying target positions and layout configurations, providing empirical foundations and actionable design guidelines for effective visualization.

Technology Category

• Computer Vision: Adversarial Attacks & Robustness
• Data Mining & Knowledge Management: Data Visualization & Summarization
• Search and Optimization: Evaluation and Analysis

Application Category

• Web Mining and Content Analysis: Web data visualization
• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

Finding a particular object in a display is important for viewers in many visualizations, for example, when reacting to brushing or to a highlighted object. This can be enabled by making the target object different in one of the visual variables that determine the object's appearance; for example, by changing its color or size. Certain interpretations of the visual search literature have promoted the view that using visual variables such as hue-often labeled as preattentive-would make the target object automatically"popout,"implying that an object can be located almost instantly, regardless of the number of objects in the display. In this paper we present a study that serves as a bridge between the extensive visual search literature and visualization, establishing empirical base measurements for the localization task. By testing displays with up to hundreds of objects, we are able to show that none of the common visual variables is immune to the increase in the number of objects. We also provide the first empirically informed comparisons between visual variables for this task in the context of visualization, and show how different visual variables have varying robustness with respect to two additional dimensions: the location of the target and the overall visual arrangement (layout). A free copy of this paper and all supplemental materials are available on our online repository: https://osf.io/z68ak/overview.

Problem

• locatability
• visual variables
• single target localization
• visual search
• preattentive

Innovation

• visual variables
• single target localization
• preattentive processing
• locatability robustness
• empirical evaluation