Personal Identification Using Footstep Detection in In-Door Environment

摘要

Footsteps, with different shoes of heels, sneakers, leathers or even bare footed, will appear in different grounds of concrete, wood, etc. If a footstep is discriminable, the application to various fields can be considered. In this paper, the feature extraction of a footstep is investigated. We focus on the recognizing a certain kind of footstep waveforms under the restricted condition. We propose a new methodology using the feature parameter such as the peak frequency set by the mel-cepstrum analysis, the walking intervals and the similarity of spectrum envelope. It is shown for personal identification that the performance of the proposed method is effective.