Feature selection based on a fuzzy complementary criterion: application to gait recognition using ground reaction forces.

Abstract:

:An efficient wavelet-based feature selection (FS) method is proposed in this paper for subject recognition using ground reaction force measurements. Our approach relies on a local fuzzy evaluation measure with respect to patterns that reveal the adequacy of data coverage for each feature. Furthermore, FS is driven by a fuzzy complementary criterion (FuzCoC) which assures that those features are iteratively introduced, providing the maximum additional contribution with regard to the information content given by the previously selected features. On the basis of the principles of FuzCoC, we develop two novel techniques. At Stage 1, wavelet packet (WP) decomposition of gaits is accomplished to obtain a set of discriminating frequency sub-bands. A computationally simple FS method is then applied at Stage 2, providing a compact set of powerful and complementary features, from WP coefficients. The quality of our approach is validated via comparative analysis against existing methods on gait recognition.

authors

Moustakidis SP,Theocharis JB,Giakas G

doi

10.1080/10255842.2011.554408

subject

Has Abstract

pub_date

2012-01-01 00:00:00

pages

627-44

issue

6

eissn

1025-5842

issn

1476-8259

pii

937779769

journal_volume

15

pub_type

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