NDLI: Footstep classification using wavelet decomposition

Content Provider	IEEE Xplore Digital Library
Author	Itai, A. Yasukawa, H.
Copyright Year	2007
Description	Author affiliation: Aichi Prefectural Univ., Nagakute (Itai, A.; Yasukawa, H.)
Abstract	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 personal identification has been confirmed by using the feature parameter of footsteps, however, it is necessary to use more effective parameters since the recognition rate of this method decreases as the number of subjects increases. In audio classification, Fourier and wavelet transform were used to extract the feature of audio signals. The feasibility of a footstep classification using Fourier and wavelet parameters were confirmed previously. In this paper, we focused on the wavelet parameter which consists of subband power, time-brightness and time-width. Previous work shows that the feature extraction using wavelet transform is effective for footstep categorizations, however, an optimal frame length for feature extraction and the relationship between a recognition rate and the length of feature parameters are not discussed in that paper. This paper provides two dominant results; the frame window size, which yield the good accuracy for footstep classification, is 4096; the feature parameter based on wavelet parameters can be reduced to 2/3 with equivalent recognition rate. Results show that the parameter applied herein yields effective and practical footstep classification.
Starting Page	551
Ending Page	556
File Size	635459
Page Count	6
File Format	PDF
ISBN	9781424409761
DOI	10.1109/ISCIT.2007.4392080
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-10-17
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Legged locomotion Wavelet domain Continuous wavelet transforms Fourier transforms Surveillance Humans Footwear Feature extraction Wavelet analysis Security
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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