On Reducing the Effect of Silhouette Quality on Individual Gait Recognition: A Feature Fusion Approach

Ning Jia, Victor Sanchez, Chang Tsun Li, Hassan Mansour

Research output: Book chapter/Published conference paperConference paper

3 Citations (Scopus)

Abstract

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.
Original languageEnglish
Title of host publicationBIOSIG 2015 - Proceedings of the 14th International Conference of the Biometrics Special Interest Group
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1-5
VolumeP-245
ISBN (Electronic)9783885796398, 9783885796398
DOIs
Publication statusPublished - 30 Oct 2015
Event14th International Conference of the Biometrics Special Interest Group: BIOSIG 2015 - Center for Applied Security Technology, Fraunhofer Institute for Computer Graphics Research, Darmstadt, Germany
Duration: 09 Sep 201511 Sep 2015
Conference number: 35550
http://fg-biosig.gi.de/biosig2015

Conference

Conference14th International Conference of the Biometrics Special Interest Group
CountryGermany
CityDarmstadt
Period09/09/1511/09/15
Internet address

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  • Cite this

    Jia, N., Sanchez, V., Li, C. T., & Mansour, H. (2015). On Reducing the Effect of Silhouette Quality on Individual Gait Recognition: A Feature Fusion Approach. In BIOSIG 2015 - Proceedings of the 14th International Conference of the Biometrics Special Interest Group (Vol. P-245, pp. 1-5). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/BIOSIG.2015.7314613