The Eye-Head Mover Spectrum: Modelling Individual and Population Head Movement Tendencies in Virtual Reality

2026-02-05

AI Summary

This study addresses the significant yet unmodeled individual differences in how people coordinate eye and head movements when shifting gaze in virtual reality (VR). Through a large-scale free-viewing experiment with 360° videos (N=87) and a controlled task (N=28), this work establishes “head-movement tendency” as a key dimension of individual variation in VR interaction. The authors propose a parametric model based on a hinge function to characterize the continuous behavioral spectrum ranging from eye-dominant to head-dominant strategies. Results demonstrate that this tendency exhibits partial stability and individual consistency across tasks, offering a theoretical foundation and practical design implications for adaptive VR systems—such as foveated rendering and viewport prediction—that can be tailored to users’ natural viewing behaviors.

Technology Category

• Humans and AI: Game Design — Virtual Humans, NPCs and Autonomous Characters
• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior
• Computer Vision: Motion & Tracking

Application Category

• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Security and Privacy: Large-scale security measurements

Abstract

People differ in how much they move their head versus their eyes when shifting gaze, yet such tendencies remain largely unexplored in HCI. We introduce head movement tendencies as a fundamental dimension of individual difference in VR and provide a quantitative account of their population-level distribution. Using a 360{\deg} video free-viewing dataset (N=87), we model head contributions to gaze shifts with a hinge-based parametric function, revealing a spectrum of strategies from eye-movers to head-movers. We then conduct a user study (N=28) combining 360{\deg} video viewing with a short controlled task using gaze targets. While parameter values differ across tasks, individuals show partial alignment in their relative positions within the population, indicating that tendencies are meaningful but shaped by context. Our findings establish head movement tendencies as an important concept for VR and highlight implications for adaptive systems such as foveated rendering, viewport alignment, and multi-user experience design.

Problem

• head movement tendencies
• individual differences
• gaze behavior
• virtual reality
• eye-head coordination

Innovation

• head movement tendencies
• gaze shift strategies
• parametric modeling
• individual differences in VR
• foveated rendering