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• W2033515237 abstract "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 (<mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M1><mml:mrow><mml:mi>x</mml:mi></mml:mrow></mml:math>), vertical axis (<mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M2><mml:mrow><mml:mi>y</mml:mi></mml:mrow></mml:math>), and temporal axis (<mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M3><mml:mrow><mml:mi>t</mml:mi></mml:mrow></mml:math>). 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." @default.
• W2033515237 created "2016-06-24" @default.
• W2033515237 creator A5027821100 @default.
• W2033515237 date "2014-01-01" @default.
• W2033515237 modified "2023-10-18" @default.
• W2033515237 title "Gait Correlation Analysis Based Human Identification" @default.
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• W2033515237 doi "https://doi.org/10.1155/2014/168275" @default.
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