Footstep classification using simple speech recognition technique

The characteristics of human footsteps are determined by the gait, the footwear and the floor. Accurate footstep analysis would be useful in various applications, home security service, surveillance and understanding of human action since the gait expresses personality, age and gender. The feasibility of a footstep classification has been confirmed by using the acoustic feature parameter[1], however, almost of conventional approaches are focused on the statistical features and pattern recognitions. In the speech recognition, a feature string is stretched and compressed in the time domain. The dynamic programming is used to accomplish this task, and is an effective method of absorbing time domain fluctuations. In the footstep classification, footstep sound (i.e. an impact sound and a fricative sound) is expanded and contracted in the time domain the same as speeches. This paper applies the DTW and cepstra to the footstep classification. Result shows that the proposed method is useful to the footstep recognition problems.