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The Scientific World Journal
Volume 2014 (2014), Article ID 168275, 8 pages
Research Article

Gait Correlation Analysis Based Human Identification

School of Computer Software, Tianjin University, Tianjin 300072, China

Received 29 August 2013; Accepted 26 November 2013; Published 29 January 2014

Academic Editors: J. Shu and F. Yu

Copyright © 2014 Jinyan Chen. 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.


Human gait identification aims to identify people by a sequence of walking images. Comparing with fingerprint or iris based identification, the most important advantage of gait identification is that it can be done at a distance. In this paper, silhouette correlation analysis based human identification approach is proposed. By background subtracting algorithm, the moving silhouette figure can be extracted from the walking images sequence. Every pixel in the silhouette has three dimensions: horizontal axis ( ), vertical axis ( ), and temporal axis ( ). By moving every pixel in the silhouette image along these three dimensions, we can get a new silhouette. The correlation result between the original silhouette and the new one can be used as the raw feature of human gait. Discrete Fourier transform is used to extract features from this correlation result. Then, these features are normalized to minimize the affection of noise. Primary component analysis method is used to reduce the features’ dimensions. Experiment based on CASIA database shows that this method has an encouraging recognition performance.