Multi-view gait fusion for large scale human identification in surveillance videos

Authors:
Emdad Hossain;Girija Chetty
Affiliations:
Faculty of Information Science and Engineering, University of Canberra, Australia;Faculty of Information Science and Engineering, University of Canberra, Australia
Venue:
ACIVS'12 Proceedings of the 14th international conference on Advanced Concepts for Intelligent Vision Systems
Year:
2012

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Abstract

In this paper we propose a novel multi-view feature fusion of gait biometric information in surveillance videos for large scale human identification. The experimental evaluation on low resolution surveillance video images from a publicly available database [1] showed that the combined LDA-MLP technique turns out to be a powerful method for capturing identity specific information from walking gait patterns. The multi-view fusion at feature level allows complementarity of multiple camera views in surveillance scenarios to be exploited for improvement of identity recognition performance.