An Explanation of Fitts' Law-like Performance in Gaze-Based Selection Tasks Using a Psychophysics Approach

Honorable Mention
Eye Tracking & Gaze InteractionUI/UX DesignersHCI Researchers

Eye gaze as an input method has been studied since the 1990s, to varied results: some studies found gaze to be more efficient than traditional input methods like a mouse, others far behind. Comparisons are often backed up by Fitts' Law without explicitly acknowledging the ballistic nature of saccadic eye movements. Using a vision science-inspired model, we here show that a Fitts'-like distribution of movement times can arise due to the execution of secondary saccades, especially when targets are small. Study participants selected circular targets using gaze. Seven different target sizes and two saccade distances were used. We then determined performance across target sizes for different sampling windows ("dwell times") and predicted an optimal dwell time range. Best performance was achieved for large targets reachable by a single saccade. Our findings highlight that Fitts' Law, while a suitable approximation in some cases, is an incomplete description of gaze interaction dynamics.

Quick Actions

Share

Share this page

ios_share

https://hci.top/en/papers/chi/4745/2019

AdRecommended

Learn AI Coding at CodeNow

At a Glance

Paper Snapshot

fact_check
dataset
Source
CHI
calendar_month
Year
2019
emoji_events
Award
Honorable Mention
group
Authors
4 authors
sell
Subtopics
Eye Tracking & Gaze Interaction
work
Professions
UI/UX Designers, HCI Researchers
article
Content Status
Abstract only
hub
Related Papers
10 related papers