Open Access

An Efficient Gait Recognition with Backpack Removal

EURASIP Journal on Advances in Signal Processing20092009:384384

Received: 12 February 2009

Accepted: 12 August 2009

Published: 4 October 2009


Gait-based human identification is a paradigm to recognize individuals using visual cues that characterize their walking motion. An important requirement for successful gait recognition is robustness to variations including different lighting conditions, poses, and walking speed. Deformation of the gait silhouette caused by objects carried by subjects also has a significant effect on the performance of gait recognition systems; a backpack is the most common of these objects. This paper proposes methods for eliminating the effect of a carried backpack for efficient gait recognition. We apply simple, recursive principal component analysis (PCA) reconstructions and error compensation to remove the backpack from the gait representation and then conduct gait recognition. Experiments performed with the CASIA database illustrate the performance of the proposed algorithm.

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Authors’ Affiliations

Biometrics Engineering Research Center, School of Electrical and Electronic Engineering, Yonsei University


© Heesung Lee et al. 2009

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.