A Hands-free Spatial Selection and Interaction Technique using Gaze and Blink Input with Blink Prediction for Extended Reality
Tim Rolff, Jenny Gabel, Lauren Zerbin, Niklas Hypki, Susanne Schmidt,, Markus Lappe, Frank Steinicke

TL;DR
This paper introduces a novel hands-free spatial interaction method using gaze and intentional eye blinks, enhanced with deep learning to improve accuracy, offering an alternative to gesture-based controls in extended reality environments.
Contribution
The paper presents a new gaze and blink-based interaction technique for XR, including a deep learning filter to reduce accidental selections, which has not been previously explored.
Findings
Gaze+Blink achieves comparable selection speeds to Gaze+Pinch.
Unintentional blinks cause false selections in Gaze+Blink.
Deep learning filtering improves interaction accuracy.
Abstract
Gaze-based interaction techniques have created significant interest in the field of spatial interaction. Many of these methods require additional input modalities, such as hand gestures (e.g., gaze coupled with pinch). Those can be uncomfortable and difficult to perform in public or limited spaces, and pose challenges for users who are unable to execute pinch gestures. To address these aspects, we propose a novel, hands-free Gaze+Blink interaction technique that leverages the user's gaze and intentional eye blinks. This technique enables users to perform selections by executing intentional blinks. It facilitates continuous interactions, such as scrolling or drag-and-drop, through eye blinks coupled with head movements. So far, this concept has not been explored for hands-free spatial interaction techniques. We evaluated the performance and user experience (UX) of our Gaze+Blink method…
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Taxonomy
TopicsGaze Tracking and Assistive Technology · Visual Attention and Saliency Detection · Advanced Computing and Algorithms
