FingerGlass: Enhancing Smart Glasses Interaction via Fingerprint Sensing

要旨

Smart glasses hold immense potential, but existing input methods often hinder their seamless integration into everyday life. Touchpads integrated into the smart glasses suffer from limited input space and precision; voice commands raise privacy concerns and are contextually constrained; vision-based or IMU-based gesture recognition faces challenges in computational cost or privacy concerns. We present FingerGlass, an interaction technique for smart glasses that leverages side-mounted fingerprint sensors to capture fingerprint images. With a combined CNN and LSTM network, FingerGlass identifies finger identity and recognizes four types of gestures (nine in total): sliding, rolling, rotating, and tapping. These gestures, coupled with finger identification, are mapped to common smart glasses commands, enabling comprehensive and fluid text entry and application control. A user study reveals that FingerGlass represents a promising step towards a fresh, discreet, ergonomic, and efficient input interaction with smart glasses, potentially contributing to their wider adoption and integration into daily life.

著者
Zhanwei Xu
Tsinghua University, Beijing, China
Haoxiang Pei
Tsinghua University, Beijing, China
Jianjiang Feng
Tsinghua University, Beijing, China
Jie Zhou
Department of Automation, BNRist, Tsinghua University, Beijing, China
DOI

10.1145/3706598.3713929

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713929

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Interaction Techniques

Annex Hall F204
7 件の発表
2025-04-28 23:10:00
2025-04-29 00:40:00
日本語まとめ
読み込み中…