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On reducing the effect of silhouette quality on individual gait recognition: a feature fusion approach

conference contribution
posted on 2015-01-01, 00:00 authored by N Jia, V Sanchez, Chang-Tsun LiChang-Tsun Li, H Mansour
© 2015 Gesellschaft für Informatik e.V. The quality of the extracted gait silhouettes can hinder the performance and practicability of gait recognition algorithms. In this paper, we propose a framework that integrates a feature fusion approach to improve recognition rate under this situation. Specifically, we first generate a dataset containing gait silhouettes with various qualities based on the CASIA Dataset B. We then fuse gallery data with different qualities and project data into embedded subspaces. We perform classification based on the Euclidean distances between fused gallery features and probe features. Experimental results show that the proposed framework can provide important improvements on recognition rate.

History

Event

Biometrics Special Interest Group. International Conference (2015 : Darmstadt, Germany)

Publisher

IEEE

Location

Darmstadt, Germany

Place of publication

Piscataway, N.J.

Start date

2015-09-09

End date

2015-09-11

ISSN

1617-5468

ISBN-13

9783885796398

Language

eng

Publication classification

E1.1 Full written paper - refereed

Copyright notice

2015, Gesellschaft für Informatik e.V.

Title of proceedings

BIOSIG 2015 : Proceedings of the International Conference of the Biometrics Special Interest Group

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