Gait Recognition Method by Combining Legs Region with Entire Gait Image

DOI

10.2991/esac-15.2015.42How to use a DOI?

Keywords

Gait recognition, Gait energy image (GEI), Region bounded by legs (RBL), Feature combination, Regularization term

Abstract

Gait recognition method based on the feature combination of gait image and its region bounded by legs is proposed. Firstly, all the Eigenvectors correspond to nonnegative Eigenvalues of the entire scatter matrix of training samples are selected to compose a lower-dimension transform space. In this transform space, in order to overcome the small-sample-size problem, a regularization term is added to each sample class covariance matrix. And a new criterion function is established. By computing this optimization problem, and the eigen-matrix is made up by some eigen-vectors. Based on this method, the features of gait image and its region bounded by legs are combined to represent gait features. Finally, three gait databases of Chinese Academy of Sciences, CASIA A, CASIA B and CASIA C, are selected and the minimum distance classifier are used to verify the effectiveness of presented method.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Kai Li
AU  - Guochao Wang
PY  - 2015/08
DA  - 2015/08
TI  - Gait Recognition Method by Combining Legs Region with Entire Gait Image
BT  - Proceedings of the 2015 International Conference on Electronic Science and Automation Control
PB  - Atlantis Press
SP  - 167
EP  - 170
SN  - 2352-538X
UR  - https://doi.org/10.2991/esac-15.2015.42
DO  - 10.2991/esac-15.2015.42
ID  - Li2015/08
ER  -