Motion cycle analysis-based method and device for identifying abnormal human behavior

The invention discloses a motion cycle analysis-based method for identifying an abnormal human behavior. The method is characterized by comprising the following steps of: acquiring human motion behavior areas to form a human motion sequence; computing one-dimensional variable curves and curve frequency spectrograms of the human motion behavior areas in the sequence; judging whether the frequency spectrograms meet a periodical condition, and if all the three frequency spectrograms do not meet the periodical condition, determining that the human behavior is the abnormal behavior; if only one frequency spectrogram meets the periodical condition, determining that the human behavior is the approximate periodical behavior; extracting one motion cycle unit of the approximate periodical behavior;performing the R transform characteristics extraction of the motion cycle unit; sending the characteristics to a single-state hidden Markov model classifier for identification; and giving an alarm when the abnormal behavior occurs. The invention also discloses a motion cycle analysis-based device for identifying an abnormal human behavior, and the device is characterized by comprising a central processing mechanism, a motion cycle extracting mechanism, a motion characteristics extracting mechanism, a classifier and an abnormal behavior alarming device. The device can identify the abnormal human behavior in a higher rate of identification and give an alarm.