Abstract

A non-contact gesture recognition algorithm for smart device application using electronic disturbance is proposed in this paper. Our method secures an enough recognition distance for real smart TV application. Input patterns of the non-contact electrometer EPIC (Electric Potential Integrated Circuit) sensors are projected into two dimensional movements in a preconditioning process. Change of surrounding electronic field caused by moving hands has been observed mainly around band of 10Hz. Butterworth IIR filter, and Kalman filter are used to minimize the signal noises. Our proposed recognition process using PCA, K-Mean, and adaptive DTW algorithms can successfully identify five different gestures with more than 90% correct classification rate.

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