FingerGlass: Enhancing Smart Glasses Interaction via Fingerprint Sensing

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.