Method, apparatus, and system for human recognition based on gait features

A wireless device of a human recognition system, comprising:

• a processor;
• a memory communicatively coupled to the processor;
• and
• a receiver communicatively coupled to the processor, wherein:
• an additional wireless device of the human recognition system is configured to transmit a first wireless signal through a wireless channel of a venue,
• the receiver is configured to receive a second wireless signal through the wireless channel,
• the second wireless signal comprises a reflection of the first wireless signal by at least one object in the venue, and
• the processor is configured for:
• obtaining a time series of channel information (CI) of the wireless channel based on the second wireless signal,
• determining a presence of a person moving in the venue based on the time series of CI (TSCI),
• extracting at least one gait feature of the person from the TSCI, and
• recognizing an identity of the person based on the at least one gait feature, wherein recognizing the identity of the person comprises classifying the person as one of known users or an unknown identity, based on a deep learning model and the at least one gait feature of the person,
• wherein the deep learning model is pre-trained to register each of the known users based on a fixed and same size of normalized spectrogram for each user.

A method of a human recognition system, comprising:

• transmitting a first wireless signal through a wireless channel of a venue;
• receiving a second wireless signal through the wireless channel, wherein the second wireless signal comprises a reflection of the first wireless signal by at least one object in the venue;
• obtaining a time series of channel information (CI) of the wireless channel based on the second wireless signal;
• determining a presence of a person moving in the venue based on the time series of CI (TSCI);
• extracting at least one gait feature of the person from the TSCI;
• and
• recognizing an identity of the person based on the at least one gait feature,
• wherein recognizing the identity of the person comprises classifying the person as one of known users or an unknown identity, based on a deep learning model and the at least one gait feature of the person,
• wherein the deep learning model is pre-trained to register each of the known users based on a fixed and same size of normalized spectrogram for each user.