DopGest: Dual-Frequency Based Ultrasonic Gesture Recognition

In-air gesture recognition is becoming a popular means of interacting with terminal devices, such as smart phones, tablets and laptops. To implement in-air gesture recognition, many methods have been researched, such as computer visionbased, RF-based, WiFi-based and ultrasonic-based. Compared to other approaches, the ultrasonic-based method shows superiorities in low-cost, robustness and so on. In this paper, we construct a dual-frequency based ultrasonic gesture recognition system called DopGest, which utilizes the Doppler Effect to recognize gestures. Our system is implemented completely on a laptop without any additional equipments, and we use two speakers and one microphone already embedded in laptop as sensors. Most of ultrasonic-based methods exploit single tone, which limit the type of gestures. For instance, they can not recognize horizontal swipe gestures. On the contrary, our system can recognize swipe left and swipe right gestures by using two high tones (18 kHz). In our system, DopGest generates two different high frequency tones from two speakers and detects Doppler Effect caused by hand movements, then it extracts features from Doppler shifts of these two high tones, since laptops generally contain at least two speakers. Compared to computervision based method, our system can work under any light conditions without extra hardware devices and with low power consumption. Experiments show that our system can achieve an average classification accuracy of 88.9%.