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Gait Correlation Analysis Based Human Identification
Author
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-01-29
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
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 ( x ), vertical axis ( y ), and temporal axis ( t ).
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.
American Psychological Association (APA)
Chen, Jinyan. 2014. Gait Correlation Analysis Based Human Identification. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1048563
Modern Language Association (MLA)
Chen, Jinyan. Gait Correlation Analysis Based Human Identification. The Scientific World Journal No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-1048563
American Medical Association (AMA)
Chen, Jinyan. Gait Correlation Analysis Based Human Identification. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1048563
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1048563