用眼神和眨眼实现无手空间交互,提升操作舒适度。
A Hands-free Spatial Selection and Interaction Technique using Gaze and Blink Input with Blink Prediction for Extended Reality
- 通过眼神+有意眨眼完成选择,配合头部动作实现连续操作
- 实验显示该方法选择速度与传统捏合手势相当
- 引入深度学习预测眨眼,减少误触,适合行动不便者
基于视线的交互技术在空间交互领域备受关注。许多方法依赖额外输入模态,如手势(例如视线+捏合),这在公共或狭小空间中不舒适,且对无法完成捏合动作的用户构成挑战。为此,我们提出一种新颖的无手眼动+眨眼交互技术,利用用户视线和有意眨眼进行选择。通过有意识眨眼实现选择,结合头部运动支持连续操作(如滚动、拖拽)。目前该概念尚未用于无手空间交互。我们通过两项用户研究评估了该方法的性能与用户体验,并在真实界面场景中与视线+捏合方法对比常见菜单任务。第一项研究表明,虽选择速度相当,但易因无意眨眼产生误选;第二项研究采用深度学习算法过滤非意图眨眼,提升了准确性。
原文摘要 · Abstract (English)
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 with two user studies and compared it with Gaze+Pinch in a realistic user interface setup featuring common menu interaction tasks. Study 1 demonstrated that while Gaze+Blink achieved comparable selection speeds, it was prone to accidental selections resulting from unintentional blinks. In Study 2 we explored an enhanced technique employing a deep learning algorithms for filtering out unintentional blinks.
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