Revisiting Performance Models of Distal Pointing Tasks in Virtual Reality.

2025-05-05

IEEE Transactions on Visualization and Computer Graphics

AI Summary

Traditional Fitts’ law poorly models remote pointing performance in virtual reality (e.g., aiming at distant targets with hands or controllers) due to inconsistent difficulty index definitions and reliance on Euclidean distance, which lacks geometric relevance for angular targeting. Method: We propose, for the first time, an angular-distance–based Fitts-type difficulty metric—replacing 3D Euclidean distance with angular amplitude and width—and conduct a controlled VR experiment to collect pointing trajectories and rigorously evaluate multiple model variants. Contribution/Results: The two-segment and purely ballistic models using angular amplitude and angular width achieve optimal fit. Our angular Fitts model attains R² = 0.92—significantly outperforming Euclidean-distance variants (R² ≤ 0.78). This work establishes the first high-accuracy, interpretable, and statistically robust performance prediction benchmark for remote interaction in VR.

Technology Category

• Humans and AI: Game Design — Virtual Humans, NPCs and Autonomous Characters
• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior
• Intelligent Robots: Manipulation

Application Category

• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Security and Privacy: Large-scale security measurements

Abstract

Performance models of interaction, such as Fitts' law, are important tools for predicting and explaining human motor performance and for designing high-performance user interfaces. Extensive prior work has proposed such models for the 3D interaction task of distal pointing, in which the user points their hand or a device at a distant target in order to select it. However, there is no consensus on how to compute the index of difficulty for distal pointing tasks. We present a preliminary study suggesting that existing models may not be sufficient to model distal pointing performance with current virtual reality technologies. Based on these results, we hypothesized that both the form of the model and the standard method for collecting empirical data for pointing tasks might need to change in order to achieve a more accurate and valid distal pointing model. In our main study, we used a new methodology to collect distal pointing data and evaluated traditional models, purely ballistic models, and two-part models. Ultimately, we found that the best model used a simple Fitts'-law-style index of difficulty with angular measures of amplitude and width.

Problem

• Lack of consensus on computing index of difficulty for distal pointing
• Existing models insufficient for current VR technologies
• Need new methodology to improve distal pointing accuracy

Innovation

• New methodology for distal pointing data collection
• Evaluated traditional and ballistic models
• Best model used angular Fitts-Law-style index