Gait recognition using wifi signals

In this paper, we propose WifiU, which uses commercial WiFi devices to capture fine-grained gait patterns to recognize humans. The intuition is that due to the differences in gaits of different people, the WiFi signal reflected by a walking human generates unique variations in the Channel State Information (CSI) on the WiFi receiver. To profile human movement using CSI, we use signal processing techniques to generate spectrograms from CSI measurements so that the resulting spectrograms are similar to those generated by specifically designed Doppler radars. To extract features from spectrograms that best characterize the walking pattern, we perform autocorrelation on the torso reflection to remove imperfection…

• NS
  National Science Foundation

  Awards: 61321491, CNS-1421407, 61472184, 1421407
• NN
  National Natural Science Foundation of China

  Awards: 61472185, 61472184, 61321491, 61373129, 61373129, 61472184, 61321491, 61472185