airFinger: Micro Finger Gesture Recognition via NIR Light Sensing for Smart Devices
Published in IEEE ICDCS, 2020
Qian Zhang, Yetong Cao, Huijie Chen, Fan Li*, Song Yang, Yu Wang, Zheng Yang, Yunhao Liu. “airFinger: Micro Finger Gesture Recognition via NIR Light Sensing for Smart Devices”. EEE 40th International Conference on Distributed Computing Systems, 2020, pp. 552-562.
Abstract:
Micro finger gesture recognition is an emerging approach to realize more friendly interaction between human and smart devices, especially for small wearable devices, such as smartwatches and virtual reality glasses. This paper proposes airFinger, a novel solution utilizing NIR light sensing to realize both real-time gesture recognition and finger tracking aiming at micro finger gestures. Using a custom NIR-based sensor with novel algorithms to capture subtle finger movements, airFinger enables to detect a rich set of micro finger gestures and track finger movements in terms of scrolling direction, velocity, and displacement. Besides, airFinger is capable of effective noise mitigation, gesture segmentation, and reducing false recognition due to the unintentional actions of users. Extensive experimental results demonstrate that airFinger has robustness against individual diversity, gesture inconsistency, and many other impacts. The overall performance reaches an average accuracy as high as 98.72% over a set of 8 micro finger gestures among 10, 000 gesture samples collected from 10 volunteers.