Sparsity-based dynamic hand gesture recognition using micro-Doppler signatures

Gang Li, Rui Zhang, Matthew Ritchie, Hugh Griffiths
2017 2017 IEEE Radar Conference (RadarConf)  
In this paper, a sparsity-driven method of micro-Doppler analysis is proposed for dynamic hand gestures recognition with radar sensors. The sparse representation of the radar signals in the time-frequency domain is achieved through the Gabor dictionary, and then the micro-Doppler features are extracted by using the orthogonal matching pursuit (OMP) algorithm and fed into classifiers for dynamic hand gesture recognition. The proposed method is validated with real data measured with a K-band
more » ... with a K-band radar. Experiment results show that the proposed method outperforms the principal component analysis (PCA) algorithm, with the recognition accuracy higher than 90%. Keywords-dynamic hand gesture recognition; micro-Doppler analysis; sparse signal representation I.
doi:10.1109/radar.2017.7944336 fatcat:mdssqo2jf5alvenbi26jtwhbeu