Ultrasound based gesture recognition

Amit Das, Ivan Tashev, Shoaib Mohammed
2017 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
In this study, we explore the possibility of recognizing hand gestures using ultrasonic depth imaging. The ultrasonic device consists of a single piezoelectric transducer and an 8 -element microphone array. Using carefully designed transmit pulse, and a combination of beamforming, matched filtering, and cross-correlation methods, we construct ultrasound images with depth and intensity pixels. Thereafter, we use a combined Convolutional (CNN) and Long Short-Term Memory (LSTM) network to
more » ... gestures from the ultrasound images. We report gesture recognition accuracies in the range 64.5-96.9%, based on the number of gestures to be recognized, and show that ultrasound sensors have the potential to become low power, low computation, and low cost alternatives to existing optical sensors.
doi:10.1109/icassp.2017.7952187 dblp:conf/icassp/DasTM17 fatcat:rpn65gmmxjc7ddewvu75d3746m